Dynamic magnetic coupling structure design method
By optimizing the magnetic coupling structure design, the problems of low coupling efficiency and high cost of dynamic wireless charging technology on AGVs have been solved, achieving stable and efficient wireless charging, which is suitable for quasi-dynamic wireless charging in logistics systems.
Patent Information
- Application Number
- CN202511582108.0
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-10-31
- Publication Date
- 2026-02-10
AI Technical Summary
The application of existing dynamic wireless charging technology in AGVs suffers from problems such as low coupling efficiency, high cost, and complex paths, resulting in low charging efficiency and poor system stability.
By designing a dynamic magnetic coupling structure, including determining the magnetic core selection, establishing a three-dimensional geometric model and performing mesh discretization, setting boundary conditions for iterative solution, and optimizing the cross-sectional area and window area of the magnetic core to maximize the coupling coefficient and improve transmission efficiency.
It enables stable wireless charging of AGVs within a limited range of movement, improves charging efficiency, reduces system costs and energy consumption, and is suitable for logistics environments of different sizes and layouts.
Smart Images
Figure CN121503022A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to wireless charging technology, and in particular to a dynamic magnetic coupling structure design method, belonging to the fields of wireless power transmission technology and warehouse logistics automation. Background Technology
[0002] With the rapid development of the modern logistics industry, automated and intelligent logistics equipment, such as Automated Guided Vehicles (AGVs), have been widely used in warehousing and factory workshops. AGVs are mainly used for material handling, distribution, and assembly in various industrial and logistics environments, greatly improving work efficiency and automation levels. However, most existing AGVs rely on batteries as their power source, requiring frequent battery replacements or recharging during long-term operation, leading to reduced efficiency in the logistics system.
[0003] Traditional wired charging methods not only affect the mobility of AGVs but can also lead to interface wear and tear due to frequent connection and disconnection, impacting system stability. Existing wireless charging technologies are mostly used for static charging, which is relatively fixed in location and has low efficiency. To overcome the shortcomings of wired and static wireless charging, dynamic wireless charging technology has emerged. Dynamic wireless charging allows AGVs to charge while moving by laying a primary coil under their travel path and installing a secondary coil on the AGV. Theoretically, this can significantly reduce AGV downtime and improve the overall efficiency of the logistics system.
[0004] However, existing dynamic wireless charging technologies still face many challenges, such as coupling efficiency, high cost and high energy consumption, and complex path coupling.
[0005] Therefore, how to provide a dynamic magnetic coupling structure design method that can dynamically adjust the secondary coil installed on the AGV during operation, thereby achieving higher charging efficiency and ensuring a more stable charging process, has become an urgent problem to be solved. Summary of the Invention
[0006] This invention provides a dynamic magnetic coupling structure design method to solve the problems of high cost, stringent requirements for the layout of AGV charging coils and coils on the driving path, and complex charging paths in the existing dynamic wireless charging technology.
[0007] The magnetic coupling design method provided by this invention enables quasi-dynamic wireless charging for stable wireless charging of AGVs within a limited range of movement. Compared to fully dynamic wireless charging systems, quasi-dynamic wireless charging offers higher coupling stability and energy transfer efficiency, while significantly reducing the area required for the primary coil and lowering costs.
[0008] To achieve the above objectives, the present invention provides a dynamic magnetic coupling structure design method, comprising: determining the core selection based on output power / secondary voltage and calculating the AP value of the constrained core; establishing a three-dimensional geometric model of the magnetic coupling coil, discretizing the solution domain in the three-dimensional geometric model using a mesh, and refining / sparsening the mesh based on the error value; setting boundary conditions according to actual working conditions and performing iterative solutions to obtain the magnetic induction intensity and core utilization rate under these conditions, wherein the convergence accuracy is controlled within 10 during the iteration process. -6 Within this range, while keeping the AP value of the constrained magnetic core constant, the coupling coefficient is maximized by changing the cross-sectional area of the magnetic core and the window area, thereby achieving optimal transmission efficiency.
[0009] As a preferred embodiment of the above technical solution, a three-dimensional geometric model of the magnetically coupled coil is established, and the solution domain in the three-dimensional geometric model is discretized by a mesh. The mesh is then refined / sparsed according to the error value, including: using tetrahedral or hexahedral meshes to discretize the solution domain in the three-dimensional geometric model; the size of the mesh is refined according to the magnetic field gradient, and the refinement trend is positively correlated with the magnetic field gradient, otherwise a sparse operation is performed.
[0010] As a preferred embodiment of the above technical solution, preferably, cells whose marked error estimates exceed the threshold of the magnetic field gradient are densified in the grid at the marked location.
[0011] As a preferred embodiment of the above technical solution, the boundary conditions are set according to the actual working conditions, including: defining the winding current density, the nonlinear BH curve of the core material, and the air domain radiation boundary conditions according to the actual working conditions.
[0012] As a preferred embodiment of the above technical solution, preferably, at least the performance indicators of transmission efficiency and output voltage stability are obtained during the iteration process. If the performance indicators are not up to standard, the AP value is recalculated.
[0013] As a preferred embodiment of the above technical solution, the recalculation of the AP value includes recalculating the AP value by adjusting variables. First, one variable is adjusted to maximize the core utilization, and then another variable is adjusted to maximize the coupling coefficient.
[0014] As a preferred embodiment of the above technical solution, if the coupling coefficient cannot be maximized, the secondary induced voltage can be increased by increasing the current to reduce the direct coupling between the primary winding and the secondary winding. Then, the coupling coefficient can be maximized by increasing the height of the side column of the magnetic core.
[0015] This invention provides a dynamic magnetic coupling structure design method, comprising: determining the core selection based on output power / secondary voltage and calculating the AP value of the constraint core; establishing a three-dimensional geometric model of the magnetic coupling coil; discretizing the solution domain in the three-dimensional geometric model using a mesh; and refining / sparsening the mesh based on the error value; setting boundary conditions according to actual working conditions and performing iterative solution, wherein the convergence accuracy is controlled within 10 during the iteration process. -6 Within this range, while keeping the AP value of the constrained magnetic core constant, the coupling coefficient is maximized by changing the cross-sectional area of the magnetic core and the window area, thus achieving optimal transmission efficiency.
[0016] The advantages of this invention are that it determines the layout of the distributed primary coil through a provided dynamic magnetic coupling structure design method, thereby achieving quasi-dynamic wireless charging for AGVs, reducing charging downtime, and improving the operational efficiency of the logistics system. Optimizing the coil layout significantly improves wireless charging efficiency, increases the number of turns in the primary coil to increase the secondary voltage, thereby increasing the utilization rate of the magnetic core and reducing the system's construction and maintenance costs. This method is applicable to logistics environments of different sizes and layouts. It can be combined with an intelligent control system to dynamically activate the coil segments, reducing system energy consumption and improving overall energy utilization. Attached Figure Description
[0017] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0018] Figure 1 The present invention provides a design flowchart for a dynamic magnetic coupling structure design method.
[0019] Figure 2 The final iterative structure diagram of the magnetic core mechanism is shown in the design diagram of the dynamic magnetic coupling structure design method provided by the present invention.
[0020] Figure 3 for Figure 2 The diagram shows the magnetic induction intensity of the structure under different air gaps δ. Detailed Implementation
[0021] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.
[0022] Figure 1 This is a schematic diagram of a process provided for an embodiment of the present invention, such as... Figure 1 As shown, it includes: Step 101: Determine the core selection based on the output power / secondary voltage and calculate the AP value of the constrained core.
[0023] Step 102: Establish a three-dimensional geometric model of the magnetic coupling coil, discretize the solution domain in the three-dimensional geometric model by using a mesh, and refine / sparse the mesh according to the error value.
[0024] Specifically, tetrahedral or hexahedral meshes are used to discretize the solution domain in the 3D geometric model; the mesh size is refined according to the magnetic field gradient, with the refinement trend being positively correlated with the magnetic field gradient, and vice versa, a sparse operation is performed. Cells whose error estimate exceeds the threshold of the magnetic field gradient are marked and the mesh is refined at the marked locations.
[0025] Step 103: Set boundary conditions according to the actual working conditions and perform iterative solution.
[0026] Specifically, the winding current density, the nonlinear BH curve of the core material, and the air domain radiation boundary conditions are defined according to the actual operating conditions.
[0027] Step 104: Determine whether the performance indicators are met after iteration. If they are met, end the design process with the current data; otherwise, redesign.
[0028] During the iteration process, at least the performance indicators of transmission efficiency and output voltage stability should be obtained. If the performance indicators are not up to standard, continue to step 105.
[0029] Step 105: Control the convergence accuracy to 10. -6 The maximum coupling coefficient is obtained by keeping the AP value of the constrained magnetic core constant.
[0030] Specifically, with the AP value remaining constant, the cross-sectional area and window area of the magnetic core are adjusted to maximize the coupling coefficient, thereby optimizing the transmission efficiency.
[0031] Step 106: If the maximum coupling coefficient cannot be obtained, adjust the AP value.
[0032] Specifically, first keep one variable constant during the AP value calculation process in step 101 while adjusting another variable. When the core utilization rate is highest, adjust the other variable until the coupling coefficient is maximum. Based on the data at this point, return to step 102 to rebuild the core model. Furthermore, the process of adjusting the AP value may also include: increasing the secondary induced voltage by increasing the current to reduce the direct coupling between the primary winding and the secondary winding, and then adjusting by increasing the height of the side post of the magnetic core to maximize the coupling coefficient.
[0033] The technical solution of this invention is now described in detail: First, clarify the core design objectives and determine the output power or secondary voltage: these two parameters directly constrain the direction of subsequent steps such as core selection and coil parameter settings. Output power reflects the energy transfer capability of the charging structure, while secondary voltage is closely related to the voltage requirements of the load and is set according to the actual application scenario.
[0034] Then, the AP value calculation stage is performed for the magnetic core model structure: Area Product (AP) is an important indicator for measuring the size and energy handling capacity of a magnetic core. It is calculated as the product of the effective cross-sectional area (Ae) and the window area (Aw) of the core (AP = Ae * Aw). During the calculation, a suitable AP value is initially estimated based on the determined output power or secondary voltage. Meanwhile, the coupling coefficient of the magnetic core is a key factor affecting energy transfer efficiency, and can be optimized by flexibly adjusting the cross-sectional area and window area. Increasing the cross-sectional area helps improve flux carrying capacity, while adjusting the window area can accommodate different winding layouts. A proper ratio of these two factors can effectively improve the coupling performance of the magnetic core and reduce leakage flux losses.
[0035] Based on the above, a 1:1 three-dimensional geometric simulation model is established. This model accurately maps the actual physical structure to ensure the reliability of the simulation results. The coil winding simulation parameters input into the three-dimensional geometric simulation model include, in addition to the number of turns, excitation source, and operating frequency, the coil wire diameter (affecting current carrying capacity and copper losses) and the winding arrangement (affecting coupling degree and distributed parameters). These parameters collectively determine the electrical characteristics of the coil and form the basis for subsequent design. The model of the main charging structure is composed of the designed magnetic core model structure and the coil winding parameters; the degree of matching between the two directly affects the overall performance.
[0036] The constructed three-dimensional geometric simulation model is further processed as follows: (1) Geometric Modeling and Mesh Generation: After establishing a three-dimensional geometric model of the magnetically coupled coil, tetrahedral or hexahedral meshes are used to discretize the solution domain. The mesh size is refined according to the magnetic field gradient, and the refinement trend is directly positively correlated with the magnetic field gradient ▽B. By marking the cells whose error estimates exceed the threshold (i.e., regions with large ▽B), the mesh is further refined (increasing the cell density) at these locations. The minimum cell size can reach 0.1 mm, and the solution domain is the region of the ferrite core and winding.
[0037] (2) Discretization of governing equations: The field domain governing equations are constructed based on Maxwell's equations, and the partial differential equations are transformed into a system of algebraic equations using the Galerkin method. For eddy current field analysis, the A-φ method is used for variable decoupling, thereby effectively reducing computational complexity.
[0038] (3) Boundary condition setting: Define the winding current density, the nonlinear BH curve of the core material and the air domain radiation boundary conditions according to the actual working conditions to ensure the equivalence between the simulation model and the physical system.
[0039] (4) Iterative solution and result post-processing: A sparse matrix solver is used to iteratively solve the linear equation system, with convergence accuracy controlled within 10. -6 Within this range. The subsequent processing module can extract key electromagnetic characteristic data such as magnetic flux density distribution cloud map, winding loss density distribution, and mutual inductance parameters, which can then be used to determine whether the performance indicators are met.
[0040] After the 3D model is processed, simulation analysis is performed on the constructed model to verify the rationality of the results. During the simulation, key performance indicators such as transmission efficiency and output voltage stability are obtained. These indicators are compared with the preset design standards to determine whether the model meets the requirements. If the results are unreasonable, such as excessively low transmission efficiency or output voltage fluctuations exceeding the allowable range, it indicates that there may be a deviation in the AP value design of the magnetic core. It is necessary to return to the "Design Estimation AP Value" step to readjust parameters such as the cross-sectional area and window area of the magnetic core until the simulation results meet the design requirements. It should be noted that the AP value itself is not changed when returning to the "Design Estimation AP Value" step. Furthermore, relying solely on the aforementioned calculation formulas for traditional tightly coupled magnetically coupled coils to design a magnetic coupling model is insufficient to support the complete design of the magnetically coupled coil. Therefore, traditional theoretical calculations based on tightly coupled magnetically coupled coils are not very useful for the magnetic coupling transmission model. This application proposes a process of incorporating simulation parameters to provide feedback and optimize design parameters.
[0041] During the optimization process, the AP value of the core was kept constant. This was achieved by changing the cross-sectional area and window area of the core to maximize the coupling coefficient of the system (first, the cross-sectional area was fixed while the window area was changed to maximize the coupling coefficient, then the cross-sectional area was changed again while the window area was fixed to maximize the coupling coefficient again). The secondary induced voltage was increased by increasing the current. After at least four simulations with these parameter changes, the coupling between the primary and secondary windings was reduced to decrease leakage inductance. Then, the height of the core's side posts was increased. This increased the AP value of the core. A new core model was then established, and simulations showed that the core utilization rate was close to 0.1T, meaning the core utilization rate reached 50%. Based on these adjustments, all parameters of the model were optimized and met the design requirements.
[0042] The design process will be illustrated using a 1kW wireless charging system as an example: First, the AP value of the magnetic core is kept constant, i.e., the cross-sectional area and window area of the core are changed to maximize the coupling coefficient of the system. In addition, the secondary induced voltage is increased by increasing the current. By consulting the current withstand value of the Litz wire winding, it can be found that the maximum current carrying capacity of 0.1*500 strand Litz wire is 19.6A. Even with a maximum primary current I1=20A and a constant turns ratio, the maximum secondary voltage V2 is only 38.4V, far below the design requirements. Therefore, the secondary voltage is increased by reducing the turns ratio. When the turns ratio is reduced to 1:1, the core parameters shown in Table 1 can be obtained through simulation. As shown in Table 1, when the turns ratio is set to 1:1, the actual simulated turns ratio is 1.85:1. Even with the primary current I1 increased to 20A, the secondary voltage V2 is only 94.4V. However, in practice, the Litz wire current must have a margin of at least 20%, i.e., the primary current I... 1max The maximum value is 15.68A. At this point, the secondary voltage still does not meet the requirements, so simply optimizing the current-voltage ratio and turns ratio is insufficient to meet the system's needs. It is necessary to improve the system's coupling coefficient by changing the core's cross-sectional area and window area. To reduce the direct coupling between the primary and secondary windings and lower leakage inductance, the height of the core's side posts needs to be increased. This will increase the AP value of the core, requiring adjustment. Specifically, one variable is kept constant during the AP value calculation process, while another variable is adjusted. When the core utilization is highest, the other variable is adjusted until the coupling coefficient is maximized. Based on this, the core model is rebuilt, and the simulation data shown in Table 2 is obtained. Specifically: At this point, it can be observed that the core utilization rate is close to 0.1T. In principle, the saturation flux of a PC95 core is 0.4T, but once it exceeds 0.3T, the core flux will fluctuate drastically. Therefore, it is generally recommended to leave a margin and not exceed 0.2T, meaning the core utilization rate has reached 50%. The final iterative structure diagram and the magnetic induction intensity under different air gap δ are shown below. Figure 2 and Figure 3 As shown.
[0043] The magnetic core structure is a U-shaped core with a certain gap, with primary and secondary windings arranged on both sides of the core structure, respectively. This flux structure fully describes the magnetic circuit distribution characteristics during the energy transmission process of the magnetically coupled coil. The main magnetic flux constitutes the main path of energy transmission, leakage flux, as a non-ideal factor, leads to energy loss, and mutual inductance flux reflects the coupling effect between the windings.
[0044] Therefore, the dynamic magnetic coupling structure design method provided by this invention can determine the layout of the distributed primary coil of the magnetic core, thereby enabling quasi-dynamic wireless charging on the magnetic core inside the AGV, reducing charging downtime and improving the operating efficiency of the logistics system.
[0045] The design method provided by this invention can improve the efficiency of wireless charging by optimizing the coil layout. By increasing the number of turns in the primary coil to increase the secondary voltage, the utilization rate of the magnetic core is increased, and the construction and maintenance costs of the system are reduced. This invention is applicable to logistics environments of different sizes and layouts. Furthermore, by combining with an intelligent control system to dynamically activate the coil segments, it can reduce system energy consumption and improve overall energy utilization.
[0046] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.
Claims
1. A dynamic magnetic coupling structure design method, characterized in that, The method includes: Determine the core selection based on the output power / secondary voltage and calculate the AP value of the constrained core; A three-dimensional geometric model of the magnetically coupled coil is established. The solution domain in the three-dimensional geometric model is discretized by a mesh. The mesh is then refined or sparsed based on the error value. Boundary conditions are set based on actual working conditions, and the solution is iteratively obtained to obtain the magnetic induction intensity and core utilization rate under these conditions. During the iteration process, the convergence accuracy is controlled within 10. -6 Within this range, while keeping the AP value of the constrained magnetic core constant, the coupling coefficient is maximized by changing the cross-sectional area of the magnetic core and the window area, thereby achieving optimal transmission efficiency.
2. The design method according to claim 1, characterized in that, The process of establishing a three-dimensional geometric model of the magnetically coupled coil involves discretizing the solution domain of the three-dimensional geometric model using a mesh, and then refining / sparsening the mesh based on the error value, including: The solution domain in the three-dimensional geometric model is discretized using tetrahedral or hexahedral meshes; The size of the mesh is refined according to the magnetic field gradient, and the refinement trend is positively correlated with the magnetic field gradient; otherwise, a sparse operation is performed.
3. The design method according to claim 2, characterized in that, Also includes: Cells whose marked error estimates exceed the threshold of the magnetic field gradient are densified in the grid at the marked location.
4. The design method according to claim 1, characterized in that, The setting of boundary conditions based on actual working conditions includes: The winding current density, the nonlinear BH curve of the core material, and the air domain radiation boundary conditions are defined based on the actual operating conditions.
5. The design method according to claim 1, characterized in that, It also includes obtaining at least the transmission efficiency and output voltage stability performance indicators during the iteration process. If the performance indicators are not up to standard, the AP value is recalculated.
6. The design method according to claim 5, characterized in that, The recalculation of the AP value includes recalculating the AP value by adjusting variables. First, one variable is adjusted to maximize the core utilization, and then another variable is adjusted to maximize the coupling coefficient.
7. The design method according to claim 6, characterized in that, If the coupling coefficient cannot be maximized, the secondary induced voltage can be increased by increasing the current to reduce the direct coupling between the primary winding and the secondary winding. The coupling coefficient can then be maximized by increasing the height of the side post of the magnetic core.