System optimization design method for parameters of three-coil coupling mechanism and wireless charging system

Abstract

The invention discloses a system optimization design method for parameters of a three-coil coupling mechanism and a wireless charging system, and the method comprises the steps: building a parameterized electromagnetic simulation model through finite element analysis FEA software according to the precise definition of an initial parameter space of the three-coil coupling mechanism according to specific application demands and design constraints; key electromagnetic characteristic parameters such as self-inductance and mutual inductance under different parameter combinations and mutual inductance values under various preset offset conditions are obtained in batches through simulation to construct a parameter-performance mapping database, accurate data are provided for subsequent optimization, and calculation complexity is reduced; establishing a system-level equivalent circuit model based on the extracted electromagnetic parameters and the selected resonance compensation topology, defining a multi-objective optimization function capable of comprehensively considering energy transmission efficiency and / or coupling coefficient stability under various offset working conditions such as axial and radial conditions, and finally performing iterative optimization on the function by adopting an advanced optimization algorithm. And determining an optimal parameter combination of the three-coil coupling mechanism.

Description

Technical Field

[0001] This invention belongs to the field of wireless power transmission technology, specifically relating to a system optimization design method for the parameters of a three-coil coupling mechanism and a wireless charging system. Background Technology

[0002] Wireless charging, with its advantages of requiring no physical connection, high automation, and strong environmental adaptability, has become a promising new charging technology. The biggest challenge currently facing mainstream resonant two-coil (transmitter / receiver) wireless power transfer technology is the impact of coupling characteristics on coil collimation accuracy (i.e., anti-biasing). In practical engineering, radial (lateral), axial (vertical), or angular displacement of devices can cause a rapid decrease in mutual inductance, resulting in reduced energy conversion efficiency, prolonged charging time, and other problems, severely impacting the user experience and exacerbating system energy consumption. Improving the mismatch resistance and energy transfer efficiency of wireless power transfer systems is a key issue that urgently needs to be addressed in this field.

[0003] This paper proposes a three-coil coupling mechanism, specifically by adding a relay resonant coil between the transmitting and receiving coils. This alters the energy coupling path, achieving a high coupling coefficient and transmission efficiency even under biased magnetic conditions. While the three-coil coupling mechanism theoretically exhibits strong anti-drift capabilities, its design complexity far exceeds that of a two-coil system, primarily due to the increased number of resonant rings and the complex relationship between mutual inductance. Coil geometry parameters (shape, radius / side length, number of turns, wire material and specifications), relative spatial arrangement (longitudinal spacing, horizontal preset displacement), and the selection of the resonant compensation network structure all profoundly and strongly influence the electromagnetic characteristics of the entire system. Existing three-winding parameter design methods mainly rely on experience, trial-and-error iteration, or local optimization, making it difficult to comprehensively consider the overall performance under multiple bias conditions (such as multi-point average efficiency and efficiency fluctuation amplitude) to achieve global optimization. This directly results in long design cycles, high R&D costs, and often fails to achieve the theoretically optimal effect in practical applications, hindering the full realization of its inherent advantages. Therefore, there is an urgent need for a novel, efficient, and systematic method for optimizing the parameters of three-winding structures. The research results of this project can be applied to practical engineering, achieving a good balance between high-efficiency transmission and distortion resistance, and promoting the development and application of high-performance wireless charging technology.

[0004] Therefore, it is necessary to design a system optimization design method for the parameters of a three-coil coupling mechanism and a wireless charging system to solve the above problems. Summary of the Invention

[0005] The technical problem to be solved by the present invention is to provide a system optimization design method for the parameters of a three-coil coupling mechanism and a wireless charging system. Through a structured, data-driven process system, the optimal geometric parameter combination and relative positional relationship of the transmitting, relaying and receiving coils are efficiently determined, thereby significantly improving the energy transmission efficiency and working stability of the system under various coil alignment misalignment conditions.

[0006] To achieve the above-mentioned technical effects, the technical solution adopted by the present invention is as follows: A system optimization design method for the parameters of a three-coil coupling mechanism includes the following steps: S1. Based on the decoupling theory of self-inductance and mutual inductance, the geometric dimensions and number of turns of the three-coil structure are separated to simplify subsequent optimization calculations. S2. Finite element simulation is used to scan different combinations of geometric dimensions to obtain the single-turn self-inductance, mutual inductance and coupling coefficient matrix. The self-inductance and mutual inductance data of each coupler at the facing and maximum offset positions are extracted from the simulation results, and the corresponding multi-dimensional parameter table is constructed. The monotonicity test of the coupling coefficient is performed on each set of geometric dimension data, and parameter combinations that do not meet the positive attenuation characteristics are eliminated. S3, based on simulation matrices and physical model formulas, calculates the total self-inductance, main mutual inductance, and coupling coefficient in multi-turn cases, and evaluates the coupling retention rate; under each set of geometric parameters, for The number of turns space is exhaustively traversed to select the number of turns combination that satisfies the constraints of minimum primary mutual inductance and maximum coupling retention rate; S4, Update the global optimal solution: When a new combination of turns is better than the current optimal value in terms of the coupling coefficient, record the corresponding geometric and turns parameters; repeat the geometric dimension and turns traversal process until all design space scans are completed, and output the global optimal parameter set; S5. The transmission efficiency and anti-offset characteristics of the optimal three-coil scheme are simulated and verified. The proposed three-coil optimized scheme is compared and analyzed with traditional two-coil and other three-coil structures in terms of coupling coefficient, offset robustness and efficiency stability, to verify its comprehensive performance advantages.

[0007] Preferably, in step S1, the geometric dimensions of the three-coil structure include the inner and outer diameters of the coils, the wire diameter, the coil width, the winding method, and the coil spacing; the number of turns parameter includes the number of turns of the transmitting, relay, and receiving coils. The specific method for parameter separation through decoupling is as follows: In the finite element simulation, the number of turns is initially kept at 1, and the self-inductance is completed for a preset combination of geometric dimensions. and mutual induction Batch scanning and storage into a library; self-inductance and mutual inductance of multi-turn systems are respectively categorized... and The results of single turns are superimposed proportionally and reused for multi-turn parameter prediction.

[0008] Preferably, in step S2, the geometric dimension scanning and multidimensional parameter table construction are as follows: Under two geometric configurations, positive alignment and maximum offset, six key sensing parameters were obtained through finite element simulation. ; A multidimensional parameter table containing geometric dimensions and electromagnetic parameters was constructed, and the monotonicity of the coupling coefficients was tested.

[0009] Furthermore, relying on the single-loop model library generated step by step in step S1, software such as COMSOL and ANSYS Maxwell were used to automatically scan it; under two typical geometric configurations, "positive alignment" and "maximum offset", six key sensing parameters were obtained through simulation calculations. The simulation data and related geometric dimensions are combined to form a multidimensional parameter table. To verify the physical validity of the model, a monotonicity test is needed on the coupling coefficients, i.e., k is smaller when biased than when arranged in the forward direction. All anomalous combinations that do not meet this condition are eliminated to ensure that subsequent optimal solutions have stable coupling decay characteristics.

[0010] Preferably, the specific method for multi-turn model calculation and turn number combination selection in step S3 is as follows: Calculate the global inductance and coupling characteristics under arbitrary combinations of turns based on the single-turn parameter table; Define the coupling retention ratio as a robustness index against offset, and perform an exhaustive or heuristic search in the turns space to filter for combinations of turns that satisfy the constraints.

[0011] Furthermore, a novel single-turn structure is proposed based on this, which can achieve arbitrary number of turns. The global inductance, coupling characteristics, and coupling coefficient k are calculated; to quantify the robustness of the bias, a coupling-preserving ratio is proposed. The method involves exhaustive or heuristic search within the number of turns space (e.g., 10-200 turns) to select combinations of turns where "the main inductor is above a predetermined lower limit" and "the maximum coupling retention rate" are achieved. This method does not require expensive simulation modules and can be solved directly using only a parameter table, which can greatly improve the efficiency and controllability of the turns dimension search.

[0012] Preferably, the specific method for updating and converging the global optimal solution in step S4 is as follows: The optimal positive coupling coefficient and its corresponding geometric and turn number parameters are continuously optimized in a two-dimensional loop based on the combination of geometric dimensions and number of turns. After the traversal is complete, output the globally optimal parameter set.

[0013] In a two-dimensional loop (geometric dimensions × number of turns combination), the global optimum is continuously optimized. The optimal coupling coefficient k is initially set to 0. The global optimum is continuously searched, and the corresponding forward coupling coefficient is calculated using the optimal winding obtained in the third step. If the coefficient is higher than the current k value, the optimal record is updated using the geometry and number of turns of this set, and the value of k is also updated. After all parameters and corresponding number of turns combinations have been traversed, the entire system reaches a global optimum. This process ensures that a three-turn optimized structure can simultaneously consider coupling strength and bias robustness within a limited design space, and effectively avoids local optimum traps.

[0014] Preferably, the specific method for simulation verification and comparative analysis in step S5 is as follows: Construct a complete resonant circuit model including matching capacitors and load, and perform finite element simulation; Simulate input and output power at center alignment and various offset positions, and plot the efficiency curve as a function of offset distance; Performance comparisons were conducted based on metrics such as maximum coupling coefficient, peak efficiency, 3dB bandwidth, and offset efficiency retention rate.

[0015] The optimal three-coil scheme obtained in step S4 was validated in a finite element environment by establishing a complete resonant circuit model including matching capacitors and loads, demonstrating its transmission efficiency and anti-offset performance. This validation involved simulating input and output power under center alignment and various lateral / longitudinal offset positions, plotting the efficiency versus offset distance curve. This scheme was then compared with traditional two-coil structures and existing three-coil designs based on key indicators such as "maximum coupling coefficient," "peak efficiency," "3dB bandwidth," and "offset efficiency retention rate," quantifying the performance gap. Finally, the comprehensive performance advantages of this optimal scheme compared to other topologies were summarized from two dimensions: electromagnetic characteristics and system efficiency, providing data support for engineering applications and subsequent research and development.

[0016] Based on the optimal three-coil scheme obtained in step S4, a complete resonant circuit model including matching capacitors and loads is constructed and verified by finite element simulation. This verification includes simulated input and output power at center alignment and various horizontal / vertical bias positions, and curves showing the variation with bias distance are plotted. On this basis, this invention uses "maximum coupling coefficient," "peak efficiency," "3dB bandwidth," and "bias efficiency maintenance rate" as main indicators to compare existing two-coil and three-coil designs, and quantitatively describes their performance differences. Finally, from the perspective of electromagnetic performance and system efficiency, the comprehensive performance advantages of the optimized design scheme compared to other structures are summarized, providing data support for its engineering application and future research and development.

[0017] Preferably, a wireless charging system includes: Equivalent AC power supply; Inverter, whose input terminal is connected to the equivalent AC power supply; A transmitter resonant network, the input of which is connected to the output of the inverter; A three-coil coupling mechanism, wherein the transmitting coil is connected to the transmitting end resonant network, and the parameters of the three-coil coupling mechanism are determined by the system optimization design method described above; The receiving end resonant network has its input end connected to the receiving coil of the three-coil coupling mechanism; A rectifier, the input of which is connected to the output of the receiving resonant network; A DC filter, the input of which is connected to the output of the rectifier; An equivalent load is connected to the output terminal of the DC filter.

[0018] Preferably, the three-coil coupling mechanism includes: A transmitting coil having a first geometric dimension and a first number of turns; The relay coil has a second geometric dimension and a second number of turns; The receiving coil has a third geometric dimension and a third number of turns; The first, second, and third geometric dimensions and the number of turns are determined by the optimization design method.

[0019] Preferably, the geometric dimensions of the transmitting coil, relay coil, and receiving coil include at least one of the following: inner diameter, outer diameter, wire diameter, coil width, and winding form.

[0020] Preferably, the transmitting end resonant network and the receiving end resonant network adopt any one of the following resonant compensation topologies: series-series (SS), series-parallel (SP), parallel-series (PS), or parallel-parallel (PP).

[0021] The beneficial effects of this invention are as follows: This method efficiently determines the optimal combination of geometric parameters and relative positional relationships of the transmitting, relaying, and receiving coils through a structured, data-driven process system, thereby significantly improving the efficiency and operational stability of energy transmission under various coil misalignment conditions. Attached Figure Description

[0022] Figure 1 This is a logic flowchart of an embodiment of the present invention; Figure 2 This is a schematic diagram of the structure of an embodiment of the present invention; Figure 3 This is a graph showing the variation of mutual inductance with the direction of synthesis according to an embodiment of the present invention; Figure 4 This is a comparison diagram of the mutual inductance offset characteristics of the coil and two-coil coupling mechanism in Embodiment 3 of the present invention as a function of the synthesis direction; Figure 5 This is a graph showing the variation of the duty cycle of the Boost converter in the three-coil and two-coil IPT systems of the present invention as a function of coil offset. Figure 6 This is an example of how the efficiency of a coil-and-two-coil IPT system varies with coil offset in Embodiment 3 of the present invention. Detailed Implementation

[0023] Example 1: A system optimization design method for the parameters of a three-coil coupling mechanism includes the following steps: S1. Based on the decoupling theory of self-inductance and mutual inductance, the geometric dimensions and number of turns of the three-coil structure are separated to simplify subsequent optimization calculations. S2. Finite element simulation is used to scan different combinations of geometric dimensions to obtain the single-turn self-inductance, mutual inductance and coupling coefficient matrix. The self-inductance and mutual inductance data of each coupler at the facing and maximum offset positions are extracted from the simulation results, and the corresponding multi-dimensional parameter table is constructed. The monotonicity test of the coupling coefficient is performed on each set of geometric dimension data, and parameter combinations that do not meet the positive attenuation characteristics are eliminated. S3, based on simulation matrices and physical model formulas, calculates the total self-inductance, main mutual inductance, and coupling coefficient in multi-turn cases, and evaluates the coupling retention rate; under each set of geometric parameters, for The number of turns space is exhaustively traversed to select the number of turns combination that satisfies the constraints of minimum primary mutual inductance and maximum coupling retention rate; S4, Update the global optimal solution: When a new combination of turns is better than the current optimal value in terms of the coupling coefficient, record the corresponding geometric and turns parameters; repeat the geometric dimension and turns traversal process until all design space scans are completed, and output the global optimal parameter set; S5. The transmission efficiency and anti-offset characteristics of the optimal three-coil scheme are simulated and verified. The proposed three-coil optimized scheme is compared and analyzed with traditional two-coil and other three-coil structures in terms of coupling coefficient, offset robustness and efficiency stability, to verify its comprehensive performance advantages.

[0024] Preferably, in step S1, the geometric dimensions of the three-coil structure include the inner and outer diameters of the coils, the wire diameter, the coil width, the winding method, and the coil spacing; the number of turns parameter includes the number of turns of the transmitting, relay, and receiving coils. The specific method for parameter separation through decoupling is as follows: In the finite element simulation, the number of turns is initially kept at 1, and the self-inductance is completed for a preset combination of geometric dimensions. and mutual induction Batch scanning and storage into a library; self-inductance and mutual inductance of multi-turn systems are respectively categorized... and The results of single turns are superimposed proportionally and reused for multi-turn parameter prediction.

[0025] Preferably, in step S2, the geometric dimension scanning and multidimensional parameter table construction are as follows: Under two geometric configurations, positive alignment and maximum offset, six key sensing parameters were obtained through finite element simulation. ; A multidimensional parameter table containing geometric dimensions and electromagnetic parameters was constructed, and the monotonicity of the coupling coefficients was tested.

[0026] Furthermore, relying on the single-loop model library generated step by step in step S1, software such as COMSOL and ANSYS Maxwell were used to automatically scan it; under two typical geometric configurations, "positive alignment" and "maximum offset", six key sensing parameters were obtained through simulation calculations. The simulation data and related geometric dimensions are combined to form a multidimensional parameter table. To verify the physical validity of the model, a monotonicity test is needed on the coupling coefficients, i.e., k is smaller when biased than when arranged in the forward direction. All anomalous combinations that do not meet this condition are eliminated to ensure that subsequent optimal solutions have stable coupling decay characteristics.

[0027] Preferably, the specific method for multi-turn model calculation and turn number combination selection in step S3 is as follows: Calculate the global inductance and coupling characteristics under arbitrary combinations of turns based on the single-turn parameter table; Define the coupling retention ratio as a robustness index against offset, and perform an exhaustive or heuristic search in the turns space to filter for combinations of turns that satisfy the constraints.

[0028] Furthermore, a novel single-turn structure is proposed based on this, which can achieve arbitrary number of turns. The global inductance, coupling characteristics, and coupling coefficient k are calculated; to quantify the robustness of the bias, a coupling-preserving ratio is proposed. The method involves exhaustive or heuristic search within the number of turns space (e.g., 10-200 turns) to select combinations of turns where "the main inductor is above a predetermined lower limit" and "the maximum coupling retention rate" are achieved. This method does not require expensive simulation modules and can be solved directly using only a parameter table, which can greatly improve the efficiency and controllability of the turns dimension search.

[0029] Preferably, the specific method for updating and converging the global optimal solution in step S4 is as follows: The optimal positive coupling coefficient and its corresponding geometric and turn number parameters are continuously optimized in a two-dimensional loop based on the combination of geometric dimensions and number of turns. After the traversal is complete, output the globally optimal parameter set.

[0030] In a two-dimensional loop (geometric dimensions × number of turns combination), the global optimum is continuously optimized. The optimal coupling coefficient k is initially set to 0. The global optimum is continuously searched, and the corresponding forward coupling coefficient is calculated using the optimal winding obtained in the third step. If the coefficient is higher than the current k value, the optimal record is updated using the geometry and number of turns of this set, and the value of k is also updated. After all parameters and corresponding number of turns combinations have been traversed, the entire system reaches a global optimum. This process ensures that a three-turn optimized structure can simultaneously consider coupling strength and bias robustness within a limited design space, and effectively avoids local optimum traps.

[0031] Preferably, the specific method for simulation verification and comparative analysis in step S5 is as follows: Construct a complete resonant circuit model including matching capacitors and load, and perform finite element simulation; Simulate input and output power at center alignment and various offset positions, and plot the efficiency curve as a function of offset distance; Performance comparisons were conducted based on metrics such as maximum coupling coefficient, peak efficiency, 3dB bandwidth, and offset efficiency retention rate.

[0032] The optimal three-coil scheme obtained in step S4 was validated in a finite element environment by establishing a complete resonant circuit model including matching capacitors and loads, demonstrating its transmission efficiency and anti-offset performance. This validation involved simulating input and output power under center alignment and various lateral / longitudinal offset positions, plotting the efficiency versus offset distance curve. This scheme was then compared with traditional two-coil structures and existing three-coil designs based on key indicators such as "maximum coupling coefficient," "peak efficiency," "3dB bandwidth," and "offset efficiency retention rate," quantifying the performance gap. Finally, the comprehensive performance advantages of this optimal scheme compared to other topologies were summarized from two dimensions: electromagnetic characteristics and system efficiency, providing data support for engineering applications and subsequent research and development.

[0033] Based on the optimal three-coil scheme obtained in step S4, a complete resonant circuit model including matching capacitors and loads is constructed and verified by finite element simulation. This verification includes simulated input and output power at center alignment and various horizontal / vertical bias positions, and curves showing the variation with bias distance are plotted. On this basis, this invention uses "maximum coupling coefficient," "peak efficiency," "3dB bandwidth," and "bias efficiency maintenance rate" as main indicators to compare existing two-coil and three-coil designs, and quantitatively describes their performance differences. Finally, from the perspective of electromagnetic performance and system efficiency, the comprehensive performance advantages of the optimized design scheme compared to other structures are summarized, providing data support for its engineering application and future research and development.

[0034] like Figure 2As shown, preferably, a wireless charging system includes: Equivalent AC power supply; Inverter, whose input terminal is connected to the equivalent AC power supply; A transmitter resonant network, the input of which is connected to the output of the inverter; A three-coil coupling mechanism, wherein the transmitting coil is connected to the transmitting end resonant network, and the parameters of the three-coil coupling mechanism are determined by the system optimization design method described above; The receiving end resonant network has its input end connected to the receiving coil of the three-coil coupling mechanism; A rectifier, the input of which is connected to the output of the receiving resonant network; A DC filter, the input of which is connected to the output of the rectifier; An equivalent load is connected to the output terminal of the DC filter.

[0035] Preferably, the three-coil coupling mechanism includes: A transmitting coil having a first geometric dimension and a first number of turns; The relay coil has a second geometric dimension and a second number of turns; The receiving coil has a third geometric dimension and a third number of turns; The first, second, and third geometric dimensions and the number of turns are determined by the optimization design method.

[0036] Preferably, the geometric dimensions of the transmitting coil, relay coil, and receiving coil include at least one of the following: inner diameter, outer diameter, wire diameter, coil width, and winding form.

[0037] Preferably, the transmitting end resonant network and the receiving end resonant network adopt any one of the following resonant compensation topologies: series-series (SS), series-parallel (SP), parallel-series (PS), or parallel-parallel (PP).

[0038] Example 2: like Figure 1 As shown, this embodiment provides a parameter optimization design method for a three-coil coupling mechanism. This method systematically integrates high-precision electromagnetic simulation and advanced optimization algorithms, and includes the following collaboratively executed steps: S1: Initial parameter space definition and high-precision electromagnetic parameter acquisition stage: S1.1: This project focuses on three coils as research objects. For different types (such as power rating, operating frequency, charging distance, maximum offset, etc.), and in conjunction with actual engineering requirements, it parameterizes various aspects including different types (circular, square, DD type, etc.), inner / outer diameter / side length, effective number of turns, wire specifications (number of Litz wires / single strand diameter), and winding patterns. Based on this, it allocates the longitudinal spacing and pre-set horizontal offset between each coil unit, and provides corresponding continuous intervals or discrete candidate value sets.

[0039] S1.2: Using three-dimensional finite element software, a parametric three-coil electromagnetic simulation model was established to reproduce the coil geometry, conductor electromagnetic properties, core material BH curve, and loss characteristics. Furthermore, the electromagnetic responses of important environmental factors such as metal shielding, dielectric impurities, and foundation materials were introduced. To facilitate subsequent automated simulation, the model was parametrically designed.

[0040] S1.3: Electromagnetic simulation was performed using a systematic sampling method within the parameter value space defined in S1.1. Each input parameter was combined, and the self-inductance value of each coil was extracted separately. The mutual inductance between the coil pairs and the coil pair Key electromagnetic parameters such as [list of parameters] are determined. Simultaneously, for multiple preset bias points exhibiting typical mismatch characteristics (covering x, y, and diagonals, from ideal alignment to maximum tolerance), the mutual inductance between each pair of coils is accurately calculated. The extracted electromagnetic parameters and their corresponding geometric and positioning parameters are combined to establish a preliminary parameter-performance mapping database. Based on previous research, this invention aims to provide precise input for subsequent system optimization through high-precision simulation. By constructing alternative models and data filtering, the direct calls to the simulation process are significantly reduced, thus decreasing the number of simulations.

[0041] S2: System-level circuit modeling and multi-objective collaborative optimization stage: S2.1: Based on the inductance (L) and mutual inductance (M) parameter matrices extracted from the offset position function in stage S1.3, and combined with the resonant compensation topology selected for the three-coil system, a complete parameterized equivalent circuit model of the three-coil wireless power transmission system is constructed in circuit-level simulation software. The electrical behavior is described by deriving analytical mathematical models based on coupled-mode theory and Kirchhoff's laws, such as the transfer function. This allows the model to more comprehensively reflect all components of the system: high-frequency power supply, inverter, transmitter resonant network, three-coil coupling mechanism represented by LM parameters, receiver resonant network, rectifier, DC filter, and equivalent load. This enables the model to dynamically reveal the changes in mutual inductance parameters caused by the relative displacement between coils, thus altering the system's electrical characteristics.

[0042] S2.2: Construction of Multi-Dimensional Optimization Objective Function and Performance Quantification Evaluation: To better evaluate the comprehensive performance of the three-winding system under various operating conditions, especially bias conditions, an optimization objective function is established based on multiple pre-defined winding bias points including ideal registration points, with energy conversion efficiency under multiple pre-set critical windings containing ideal registration points as the optimization objective. The best approach is to construct this problem as a multi-objective optimization problem with an illustrative objective function: Objective 1 (Maximize average efficiency): Maximize the end-to-end energy transfer efficiency across the entire predetermined bias operation range.

[0043] Objective 2 (Maximize efficiency stability): Minimize the fluctuation of transmission efficiency within a predetermined offset range.

[0044] Objective 3 (Coupling strength / voltage / current constraints or optimization): Ensure that the key coupling coefficients of the system remain within a pre-defined ideal range under a certain bias state, and constrained by electrical parameters such as system voltage gain and current stress.

[0045] Based on this, by combining constraint methods and Pareto optimization methods, effective coordination of multiple objectives can be achieved.

[0046] S2.3: Based on this, the Particle Swarm Optimization (PSO) algorithm, suitable for solving complex multivariate optimization problems, is selected and combined with Sequential Quadratic Programming (SQP). The optimal geometric and relative position parameters defined in S1.1 are used as decision variables for iterative search. During each iteration evaluation: (a) The optimization algorithm generates a new set of candidate parameter combinations.

[0047] (b) For this parameter combination, especially the mutual inductance values ​​at each offset point, the corresponding electromagnetic parameters are quickly estimated by querying the database constructed in S1.3 and using the radial basis function network (RBFN) interpolation / fitting technique.

[0048] (c) Using one or more objective function values ​​determined by S2.1, evaluate them by circuit simulation or analytical calculation.

[0049] (d) Based on the fitness value of the evaluation results, the population or addressing point is updated through internal mechanisms to achieve the optimal combination of parameters.

[0050] S2.4: After the optimization algorithm reaches the upper limit of the number of iterations or stagnates, it outputs a Pareto optimal solution set corresponding to the three-coil coupling structure parameter combination. The designer can then select the final design scheme based on the specific requirements of the project, prioritizing either average efficiency or efficiency stability. Finally, the selected optimized design scheme is verified: FEA software is used for more detailed electromagnetic simulation to confirm its L and M parameters, and a full-system simulation is performed in a circuit simulation environment to verify its electrical performance. If conditions permit, a physical prototype is fabricated for experimental testing and verification.

[0051] Example 3: Based on the proposed parameter optimization method, a three-coil coupling mechanism for a wireless power transmission system is designed according to relevant indicators. The minimum transmission distance is 100mm, with X, Y, and Z axis offset distances of 75mm, 100mm, and 50mm, respectively. Details are shown in Table 1. Table 1: Boundary conditions;

[0052] To reduce the current in the primary and secondary coils, The design needs to be at least for ,Right now The coupling coefficient needs to reach the coupling coefficient in the aligned state. Therefore, there is The optimal parameters of the three-coil coupling mechanism are obtained from the above optimization steps, as shown in Table 2.

[0053] Table 2: Optimal parameters of the three-coil coupling mechanism;

[0054] Through simulation, the variation curves of mutual inductance and resultant direction offset of the optimal three-coil coupling mechanism, couplers 13 and 23 are obtained as follows: Figures 3-6 As shown. The change curves indicate that, due to... and The first half of the composite direction shift is almost identical; therefore, when the composite direction shift is 67.3 mm, M decreases by only 3.1%. In the second half of the composite direction shift, The slope decreases, while The slope remains stable. Therefore, when the shift in the synthesis direction increases further, M drops sharply by 32.1%. and The different trends in the latter half of the synthesis direction shift can be explained by the fact that the size of coil 2 is much smaller than that of coil 1. When the coil shift is large, the coupling between coil 2 and coil 3 is weaker. It will change slowly with the offset. Conversely, the coupling between coil 1 and coil 3 remains strong, therefore The rate of decrease was basically consistent with the first half. In summary, the range of variation for M is much smaller than... Wireless power transfer systems using the optimal three-coil coupling structure have better anti-offset capability compared to systems using two-coil couplers.

Claims

1. A system optimization design method for the parameters of a three-coil coupling mechanism, characterized in that, Includes the following steps: S1. Based on the decoupling theory of self-inductance and mutual inductance, the geometric dimensions and number of turns of the three-coil structure are separated to simplify subsequent optimization calculations. S2. Finite element simulation is used to scan different geometric size combinations to obtain the single-turn self-inductance, mutual inductance and coupling coefficient matrix. The self-inductance and mutual inductance data of each coupler at the facing and maximum offset positions are extracted from the simulation results, and the corresponding multi-dimensional parameter table is constructed. For each set of geometric dimension data, the monotonicity of the coupling coefficient is checked, and parameter combinations that do not meet the positive decay characteristics are eliminated; S3, based on simulation matrices and physical model formulas, calculates the total self-inductance, main mutual inductance, and coupling coefficient in multi-turn cases, and evaluates the coupling retention rate; under each set of geometric parameters, for The number of turns space is exhaustively traversed to select the number of turns combination that satisfies the constraints of minimum primary mutual inductance and maximum coupling retention rate; S4, Update the global optimal solution: When a new combination of turns is better than the current optimal value in terms of the coupling coefficient, record the corresponding geometric and turns parameters; repeat the geometric dimension and turns traversal process until all design space scans are completed, and output the global optimal parameter set; S5. The transmission efficiency and anti-offset characteristics of the optimal three-coil scheme are simulated and verified. The proposed three-coil optimization scheme is compared and analyzed with traditional two-coil and other three-coil structures in terms of coupling coefficient, offset robustness and efficiency stability, to verify its comprehensive performance advantages.

2. The system optimization design method for the parameters of a three-coil coupling mechanism according to claim 1, characterized in that, In step S1, the geometric dimensions of the three-coil structure include the inner and outer diameters of the coils, wire diameter, coil width, winding method, and coil spacing; the number of turns parameter includes the number of turns of the transmitting, relay, and receiving coils. The specific method for parameter separation through decoupling is as follows: In the finite element simulation, the number of turns is initially kept at 1, and the self-inductance is completed for a preset combination of geometric dimensions. and mutual induction Batch scanning and storage into a library; self-inductance and mutual inductance of multi-turn systems are respectively categorized... and The results of single turns are superimposed proportionally and reused for multi-turn parameter prediction.

3. The system optimization design method for the parameters of a three-coil coupling mechanism according to claim 2, characterized in that, In step S2, the geometric dimension scanning and multidimensional parameter table construction are as follows: Under two geometric configurations, positive alignment and maximum offset, six key sensing parameters were obtained through finite element simulation. ; A multidimensional parameter table containing geometric dimensions and electromagnetic parameters was constructed, and the monotonicity of the coupling coefficients was tested.

4. The system optimization design method for the parameters of a three-coil coupling mechanism according to claim 3, characterized in that, The specific method for multi-turn model calculation and turn number combination selection in step S3 is as follows: Calculate the global inductance and coupling characteristics under arbitrary combinations of turns based on the single-turn parameter table; Define the coupling retention ratio as a robustness index against offset, and perform an exhaustive or heuristic search in the turns space to filter for combinations of turns that satisfy the constraints.

5. The system optimization design method for the parameters of a three-coil coupling mechanism according to claim 4, characterized in that, The specific method for updating and converging the global optimal solution in step S4 is as follows: The optimal positive coupling coefficient and its corresponding geometric and turn number parameters are continuously optimized in a two-dimensional loop based on the combination of geometric dimensions and number of turns. After the traversal is complete, output the globally optimal parameter set.

6. The system optimization design method for the parameters of a three-coil coupling mechanism according to claim 5, characterized in that, The specific method for simulation verification and comparative analysis in step S5 is as follows: Construct a complete resonant circuit model including matching capacitors and load, and perform finite element simulation; Simulate input and output power at center alignment and various offset positions, and plot the efficiency curve as a function of offset distance; Performance comparisons were conducted based on metrics such as maximum coupling coefficient, peak efficiency, 3dB bandwidth, and offset efficiency retention rate.

7. A wireless charging system, characterized in that, include: Equivalent AC power supply; Inverter, whose input terminal is connected to the equivalent AC power supply; A transmitter resonant network, the input of which is connected to the output of the inverter; A three-coil coupling mechanism, wherein the transmitting coil is connected to the transmitting end resonant network, and the parameters of the three-coil coupling mechanism are determined by the system optimization design method according to any one of claims 1 to 6; The receiving end resonant network has its input end connected to the receiving coil of the three-coil coupling mechanism; A rectifier, the input of which is connected to the output of the receiving resonant network; A DC filter, the input of which is connected to the output of the rectifier; An equivalent load is connected to the output terminal of the DC filter.

8. A wireless charging system according to claim 7, characterized in that, The three-coil coupling mechanism includes: A transmitting coil having a first geometric dimension and a first number of turns; The relay coil has a second geometric dimension and a second number of turns; The receiving coil has a third geometric dimension and a third number of turns; The first, second, and third geometric dimensions and the number of turns are determined by the optimization design method.

9. A wireless charging system according to claim 8, characterized in that, The geometric dimensions of the transmitting coil, relay coil, and receiving coil include at least one of the following: inner diameter, outer diameter, wire diameter, coil width, and winding method.

10. A wireless charging system according to claim 9, characterized in that, The transmitter resonant network and receiver resonant network adopt any one of the following resonant compensation topologies: series-series SS, series-parallel SP, parallel-series PS, or parallel-parallel PP.

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