An optimization method for multi-coil array arrangement in a magnetically coupled wireless power transmission system

Abstract

The present invention provides a method for optimizing the arrangement of multiple coil arrays in a magnetically coupled wireless power transmission system, comprising the following steps: establishing a parameterized finite element simulation model of a multiple transmitting coil array for wireless power transmission based on the wireless power transmission system; and using a genetic algorithm to perform an optimization solution based on the finite element simulation model of the multiple transmitting coil array for wireless power transmission, with the objective function of maximizing the efficiency η of the wireless power transmission system and the position of the center of the transmitting coil as a constraint condition, to obtain and output the optimal parameters for the position of the center of the ray coil, thereby obtaining the optimal arrangement of the transmitting array when the transmission performance of the charging area of the magnetically coupled resonant wireless power transmission system is optimal. This method solves the problem in existing wireless power transmission systems where multiple transmitting coils influence each other and it is difficult to obtain an array arrangement with optimal system efficiency, thereby achieving optimal transmission performance in the charging area and obtaining the optimal arrangement of the transmitting array.

Description

Technical Field

[0001] The present invention belongs to the technical field of wireless power transmission, and in particular relates to a method for optimizing the arrangement of a multi-coil array in a magnetically coupled wireless power transmission system. Background Art

[0002] Wireless power transmission technology holds broad application prospects. It can be used not only for charging household appliances and electric vehicles, but also in aerospace, oilfield drilling, medical equipment, and other challenging environments, demonstrating its immense value and profound research significance. Wireless power transmission can be broadly categorized into three types: electromagnetic induction wireless power transmission, microwave wireless power transmission, and magnetic coupling resonant wireless power transmission. For many years, scientists both domestically and internationally have diligently conducted extensive research on wireless power transmission technology, but progress has been slow. In recent years, magnetic coupling resonant wireless power transmission has rapidly developed as an emerging wireless power transmission technology, generating significant buzz in the field. Currently, this technology holds the greatest potential for application in wireless power transmission.

[0003] However, the current mainstream wireless charging method for electronic devices is one-to-one, that is, one charging station corresponds to one receiving device. This not only makes it difficult to deal with the reduced charging efficiency caused by the misalignment of the two positions, but also cannot meet the growing demand for wireless charging in public places with heavy traffic. Wireless charging platforms that support multiple loads and arbitrary receiving locations will be a major development trend in the future.

[0004] Compared to single-source WPT systems, multi-source WPT (wireless power transfer) systems require more considerations. Currently, the placement of multiple transmitting coil arrays often relies on empirical selection of transmitting coil positions, making it difficult to achieve optimal placement. Low-frequency electromagnetic field finite element software Maxwell, with its comprehensive functional modules and high computational accuracy, is an excellent simulation method for coil design. However, its inherent optimization capabilities are limited in precision. Summary of the Invention

[0005] In order to solve the problem of difficulty in reasonably selecting the arrangement of the transmitting coil array in the prior art, the present invention provides a technical solution adopted by the present invention: a method for optimizing the arrangement of a multi-coil array of a magnetically coupled wireless power transmission system, comprising the following steps:

[0006] According to the wireless power transmission system, a parameterized wireless power transmission multi-transmitting coil array finite element simulation model is established;

[0007] Based on the finite element simulation model of a wireless power transmission multi-transmitting coil array, a genetic algorithm is used for optimization and solution, with the objective function of maximizing the efficiency η of the wireless power transmission system and the position of the center of the transmitting coil as the constraint condition. The optimal parameters of the center position of the ray coil are obtained and output, and then the optimal arrangement of the transmitting array is obtained when the transmission performance of the charging area of the magnetically coupled resonant wireless power transmission system is optimal.

[0008] Furthermore, the transmitting coil array suitable for the magnetically coupled resonant wireless power transmission system includes at least two planar spiral coils, and the receiving coil adopts one planar spiral coil.

[0009] Furthermore, the process of using the genetic algorithm to obtain and output the optimal parameters of the center position of the ray circle is as follows:

[0010] S21: setting the population number and genetic generation number, and generating an initial population according to the population number and genetic generation number;

[0011] S22: Modify the position parameters to be optimized in the finite element simulation model of the wireless power transmission multi-transmitting coil array, and perform finite element simulation;

[0012] S23: Calculate the objective function value based on the finite element simulation results; determine whether the iteration has converged based on the objective function value. If the iteration has not converged, return to S2 to modify the position parameters to be optimized in the finite element simulation model of the wireless power transmission multi-transmitting coil array and perform the finite element simulation step; stop the iteration when it converges. After the iteration stops, calculate the efficiency of the wireless power transmission system based on the optimized position parameters; determine whether the efficiency of the wireless charging system meets the preset requirements. If so, determine the optimal position parameters and output them.

[0013] Furthermore, the objective function for maximizing the efficiency η of the wireless power transmission system is:

[0014]

[0015] Among them, I1, I2, I3, I4 are the transmitting coil currents, U S1 , U S2 , U S3 , U S4 is the input voltage of the transmitting coil, I5 is the current of the receiving coil, R L is the load equivalent resistance.

[0016] Furthermore, according to the wireless power transmission system, a parameterized wireless power transmission multi-transmitting coil array finite element simulation model is established using Maxwell software.

[0017] Furthermore: the genetic algorithm is optimized using the Matlab calculation process.

[0018] The present invention provides an optimization method for the multi-coil array arrangement of a magnetically coupled wireless power transmission system. This method considers the overall optimization of the coupling between the transmitting array and the receiving coil, rather than optimizing the coupling of each transmitting coil and the receiving coil individually. This method can reduce the dependence of transmission efficiency on the receiving position. All processes are fully automated, without human intervention and the possibility of errors in the intermediate processes, greatly improving the accuracy of the results. The method combines the advantages of Matlab in simple object-oriented programming and powerful data analysis capabilities with the advantages of Maxwell finite element analysis, improves the consistency of analysis methods for different sample simulation data, and significantly reduces the time cost of data analysis. A genetic algorithm is used to solve the objective function containing multiple parameters to obtain the optimal solution for the wireless power transmission multi-transmitter array arrangement, improving the robustness of the system and solving the problem in existing wireless power transmission systems where multiple transmitting coils influence each other and it is difficult to obtain an array arrangement with optimal system efficiency. The method achieves optimal transmission performance in the charging area and obtains the optimal arrangement of the transmitting array. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the 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 labor.

[0020] Figure 1 is a flow chart of the present method;

[0021] Figure 2 It is a topological structure diagram;

[0022] Figure 3 It is the joint simulation flow chart;

[0023] Figure 4 It is a data transmission flow chart. DETAILED DESCRIPTION

[0024] It should be noted that, unless there is any conflict, the embodiments of the present invention and the features in the embodiments may be combined with each other. The present invention will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0025] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. The following description of at least one exemplary embodiment is actually only illustrative and is in no way intended to limit the present invention and its application or use. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0026] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit the exemplary embodiments according to the present invention. As used herein, unless the context clearly indicates otherwise, the singular form is intended to include the plural form. In addition, it should be understood that when the terms "comprise" and / or "include" are used in this specification, they indicate the presence of features, steps, operations, devices, components and / or combinations thereof.

[0027] Unless otherwise specifically stated, the relative arrangement of the parts and steps, numerical expressions and numerical values described in these embodiments do not limit the scope of the present invention. At the same time, it should be clear that, for ease of description, the sizes of the various parts shown in the drawings are not drawn according to the actual proportional relationship. The techniques, methods and equipment known to ordinary technicians in the relevant fields may not be discussed in detail, but where appropriate, the techniques, methods and equipment should be considered as part of the authorization specification. In all examples shown and discussed here, any specific value should be interpreted as merely exemplary and not as a limitation. Therefore, other examples of the exemplary embodiments may have different values. It should be noted that similar numbers and letters represent similar items in the following figures, so once an item is defined in one figure, it does not need to be further discussed in subsequent figures.

[0028] In the description of the present invention, it should be understood that the directions or positional relationships indicated by directional words such as "front, back, up, down, left, right", "horizontal, vertical, vertical, horizontal" and "top, bottom" are usually based on the directions or positional relationships shown in the accompanying drawings. They are only for the convenience of describing the present invention and simplifying the description. Unless otherwise specified, these directional words do not indicate or imply that the device or element referred to must have a specific direction or be constructed and operated in a specific direction. Therefore, they cannot be understood as limiting the scope of protection of the present invention: the directional words "inside and outside" refer to the inside and outside relative to the outline of each component itself.

[0029] For ease of description, spatially relative terms such as "above", "above", "on the upper surface of", "above", etc. may be used herein to describe the spatial positional relationship of a device or feature to other devices or features as shown in the figures. It should be understood that spatially relative terms are intended to include different orientations of the device in use or operation in addition to the orientation described in the figures. For example, if the device in the drawings is inverted, the device described as "above other devices or structures" or "above other devices or structures" will be positioned as "below other devices or structures" or "below their position devices or structures". Thus, the exemplary term "above" can include both "above" and "below". The device can also be positioned in other different ways (rotated 90 degrees or in other orientations), and the spatially relative descriptions used here are interpreted accordingly.

[0030] In addition, it should be noted that the use of terms such as "first" and "second" to limit components is only for the convenience of distinguishing the corresponding components. Unless otherwise stated, the above terms have no special meaning and therefore cannot be understood as limiting the scope of protection of the present invention.

[0031] A method for optimizing the arrangement of multiple transmitting coil arrays in a magnetically coupled resonant wireless power transmission system. This method is applicable to a transmitting coil array in a magnetically coupled resonant wireless power transmission system, comprising at least two planar spiral coils and a receiving coil employing a single planar spiral coil. In an embodiment of the present application, the transmitting coil array comprises four planar spiral coils, and the receiving coil comprises a single identical planar spiral coil. Nine test points are selected on the plane where the receiving coils are located.

[0032] Figure 1 : is a flow chart of the present method; the method comprises the following steps:

[0033] S1: According to the wireless power transmission system, a parameterized wireless power transmission multi-transmitting coil array finite element simulation model is established;

[0034] S2: Based on the finite element simulation model of the wireless power transmission multi-transmitting coil array, with the objective function of maximizing the efficiency η of the wireless power transmission system and the position of the center of the transmitting coil as the constraint condition, a genetic algorithm is used to obtain the optimal parameters for determining the position and output them, thereby obtaining the optimal arrangement of the transmitting array when the transmission performance of the charging area of the magnetically coupled resonant wireless power transmission system is optimal.

[0035] S1 and S2 are performed sequentially;

[0036] Furthermore, when the average efficiency of the receiving plane test point is the largest, the transmission performance of the charging area of the magnetic coupling resonant wireless power transmission system is the best.

[0037] Figure 2 This is a topological diagram, ignoring the mutual inductance between the transmitting coils. Figure 2 List the transmit circuit impedances Z1, Z2, Z3, Z4 and the receive circuit impedance Z5 as follows:

[0038]

[0039] According to Kirchhoff's law, the voltage equations of the five circuits are as follows:

[0040]

[0041] Arranging the above formula, we can get the expressions of the current in the five loops:

[0042]

[0043] The objective function for maximizing the efficiency η of the wireless power transmission system is:

[0044]

[0045] Among them, M 15 、M 25 、M 35 、M 45 Respectively represent the mutual inductance between the transmitting coil and the receiving coil. S1 、U S2 、U S3 、U S4 are the transmitter input voltage sources, L1, L2, L3, and L4 are transmitter inductors, L5 is receiver inductors, C1, C2, C3, and C4 are transmitter resonant compensation capacitors, C5 is receiver resonant compensation capacitor, R1, R2, R3, and R4 are transmitter loop impedances, R5 is receiver loop impedance, R L is the load impedance, I1, I2, I3, and I4 are the transmitter loop currents, and I5 is the receiver loop current.

[0046] Then the position parameters are iteratively optimized to obtain the position parameters when the objective function is maximized.

[0047] Furthermore, based on the finite element simulation, optimization is performed according to the operation flow of the genetic algorithm in Matlab. The process of using the genetic algorithm to obtain the optimal parameters of the center position of the ray circle and outputting them is as follows:

[0048] S21: setting the population number and genetic generation number, and generating an initial population according to the population number and genetic generation number;

[0049] S22: Modify the position parameters to be optimized in the finite element simulation model of the wireless power transmission multi-transmitting coil array, and perform finite element simulation;

[0050] S23: Calculate the objective function value based on the finite element simulation results; determine whether the iteration converges based on the objective function value. If the iteration does not converge, return to S22 to modify the position parameters to be optimized in the finite element simulation model of the wireless power transmission multi-transmitting coil array and perform the finite element simulation step; stop the iteration when it converges. After the iteration stops, calculate the efficiency of the wireless power transmission system based on the optimized position parameters; determine whether the efficiency of the wireless charging system meets the preset requirements. If so, determine the optimal position parameters and output them.

[0051] Furthermore, according to the wireless power transmission system, a parameterized wireless power transmission multi-transmitting coil array finite element simulation model is established using Maxwell software.

[0052] Furthermore: the genetic algorithm is optimized using the Matlab calculation process. Figure 3 Co-simulation flow chart; the specific process of MATLAB calling MAXWELL in the genetic algorithm is as follows:

[0053] S21: MATLAB generates the initial population within the constraints and writes it to the datain.txt file;

[0054] S22: MATLAB calls MAXWELL, which reads the parameters in the datain.txt file and completes the finite element solution;

[0055] S23: MAXWELL outputs the calculated mutual inductance value to the dataout.txt file;

[0056] S24: MATLAB reads the data in the dataout.txt file and brings it into the fitness function to determine whether the iteration termination condition is met;

[0057] S25: If the iteration termination condition is not met, a new initial population is generated through selection, crossover, and mutation, which overwrites the original initial population and is saved in the datain.txt file;

[0058] S26: If the iteration termination condition, i.e., the maximum number of iterations, is reached, the result is output and the optimization ends.

[0059] The joint simulation of Matlab and Maxwell is realized through the file operation functions of the two. The specific data transmission process is as follows: Figure 4 shown.

[0060] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the above embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements 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 method for optimizing the arrangement of a multi-coil array in a magnetically coupled wireless power transmission system, characterized in that: The following steps are involved: According to the wireless power transmission system, a parameterized wireless power transmission multi-transmitting coil array finite element simulation model is established; Based on the finite element simulation model of a wireless power transmission multi-transmitting coil array, a genetic algorithm was used to optimize the system efficiency η, with the objective function of maximizing the center position of the transmitting coil as a constraint. The parameters of the center position of the transmitting coil were obtained, and the optimal arrangement of the transmitting array for the best transmission performance in the charging area of the magnetically coupled resonant wireless power transmission system was obtained. The process of using the genetic algorithm to obtain the optimal parameters of the center position of the ray circle is as follows: S21: setting the population number and genetic generation number, and generating an initial population according to the population number and genetic generation number; S22: Modify the position parameters to be optimized in the finite element simulation model of the wireless power transmission multi-transmitting coil array, and perform finite element simulation; S23: Calculate the objective function value according to the finite element simulation results; Determining whether the iteration has converged based on the objective function value; if the iteration has not converged, returning to S2 to modify the position parameters to be optimized in the finite element simulation model of the wireless power transmission multi-transmitting coil array and performing the finite element simulation step; stopping the iteration when it has converged, and after stopping the iteration, calculating the efficiency of the wireless power transmission system based on the optimized position parameters; determining whether the efficiency of the wireless charging system meets the preset requirements, and if so, determining and outputting the optimal position parameters; The objective function for maximizing the efficiency η of the wireless power transmission system is: （4） Among them, I1, I2, I3, I4 are the transmitting coil currents, U S1 , U S2 , U S3 , U S4 is the input voltage of the transmitting coil, I5 is the current of the receiving coil, R L is the load equivalent resistance.

2. The method for optimizing the arrangement of a multi-coil array in a magnetically coupled wireless power transmission system according to claim 1, wherein: The transmitting coil array suitable for the magnetic coupling resonant wireless power transmission system includes at least two planar spiral coils, and the receiving coil adopts one planar spiral coil.

3. The method for optimizing the arrangement of a multi-coil array in a magnetically coupled wireless power transmission system according to claim 1, wherein: According to the wireless power transmission system, a parameterized wireless power transmission multi-transmitting coil array finite element simulation model is established using Maxwell software.

4. The method for optimizing the arrangement of a multi-coil array in a magnetically coupled wireless power transmission system according to claim 1, wherein: The genetic algorithm is optimized using the Matlab calculation process.

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