METHOD AND SYSTEM FOR ASSISTING IN THE MANUFACTURING OF AN ENERGY RECEIVER ELEMENT FOR A WIRELESS ELECTRICAL ENERGY TRANSFER SYSTEM.

Abstract

This disclosure relates to a system and method for assisting in the manufacturing of an electrical energy receiving element. The method includes: obtaining (201) a representative input data set of characteristics of a reference electrical energy receiving element, referred to as the second receiving element, and a predetermined overall temperature; determining (202) an initial copper-iron loss distribution; and performing (204, 205, 206) an iterative optimization of a temperature distribution and updating the copper-iron loss distribution from said temperature distribution until their respective values ​​stabilize; and then determining (207) a representative output data set of electromagnetic, thermal, and electrical power transmission behavior; and determining and exporting (208) a set of manufacturing parameters for said second receiving element.It is possible to design an optimized energy-receiving element, that is, one whose mass is reduced while maintaining a performance level at least equivalent to that of a conventional energy-receiving element. Figure to be published with the abbreviation: Fig. 2.

Description

Title of the invention: METHOD AND SYSTEM FOR ASSISTANCE IN THE MANUFACTURE OF AN ENERGY RECEIVER ELEMENT FOR A WIRELESS ELECTRICAL ENERGY TRANSFER SYSTEM. Technical field

[0001] The scope of this disclosure relates to wireless power transfer using a wireless power transfer system. More specifically, this disclosure relates to a method for assisting in the manufacture of a power receiver element of the wireless power transfer system. This power receiver element is installed in a vehicle, particularly an aircraft. STATE OF PRIOR ART

[0002] In order to reduce CO2 emissions and noise pollution in airport areas, electric motors can be placed at the level of the landing gear of an aircraft (for example: nose landing gear of the aircraft, and main landing gear), in order to carry out all the operational phases taking place on the taxiways of aircraft in electric mode.

[0003] To power the batteries of these electric motors, wireless electrical power transfer systems have been developed. Figure 1 schematically illustrates a front view of an example of a wireless electrical power transfer system. This wireless electrical power transfer system comprises: an electrical power receiver element ER carried on board the aircraft, and an electrical power transmitter element EE embedded in the ground of the taxiways. The electrical power transmitter element EE is configured to transfer electrical power in the form of a magnetic field to the electrical power receiver element ER when the latter is positioned opposite said electrical power transmitter element EE.The electrical energy receiving element ER then converts the electrical power received from the electrical energy emitting element EE and transmits this converted electrical power to the batteries powering the electric motors (not shown in [Fig.1]).

[0004] The electrical energy emitting element EE and the electrical energy receiving element ER comprise several components such as: an enclosure 101R, 101E into which coils 102R, 102E are inserted, a ferromagnetic element 103R, 103E and an aluminium plate 104R, 104E having an electrical shielding function.

[0005] This ferromagnetic element 103R is used so that the magnetic field generated by the electrical energy emitting element EE can close around the coils 102R of the electrical energy receiving element ER. It is thus possible to constrain the magnetic field generated by the electrical energy emitting element EE and to limit the losses of magnetic energy.

[0006] This ferromagnetic element 103R is generally composed of ferrites, for example in the form of parallelepiped tiles placed side by side. The ferrites have a high mass density, representing approximately one-third of the total mass of the electrical energy receiving element ER carried in the aircraft.

[0007] Furthermore, after modeling the magnetic field at the level of the ferromagnetic element 103R of the electrical energy receiving element ER, it can be observed that the use of ferrites is not optimized because the levels of the magnetic field are inhomogeneous, or even detrimental in certain areas of the ferromagnetic element 103R.

[0008] It is therefore desirable to overcome these drawbacks of the prior art.

[0009] It is particularly desirable to provide a solution which makes it possible to reduce the weight of the electrical energy receiving element while maintaining high performance in terms of power transmitted to the batteries of the electric motors and the efficiency of transmitting this power. Description of the invention

[0010] A method for assisting in the fabrication of an electrical energy receiving element, hereinafter referred to as the second receiving element, is proposed herein. This second receiving element is configured to cooperate with an electrical energy emitting element such that the second receiving element and the electrical energy emitting element form an electrical energy transfer system designed to allow the transfer of electrical energy in the form of a magnetic field from the electrical energy emitting element to the second receiving element. The method is implemented by a fabrication assistance system in the form of electronic circuitry. The method comprises: - to obtain a representative set of input data for the characteristics of a reference electrical energy receiving element, hereinafter referred to as the first receiving element, and a predetermined overall temperature of said first receiving element, - determine an initial distribution of copper-iron losses relative to said first receiving element, based on said input data set and said predetermined global temperature, - to perform an iterative optimization of a temperature distribution and update the copper-iron loss distribution from this temperature distribution until their respective values ​​stabilize, - to determine, from the copper-iron loss distribution and the temperature distribution after optimization, a set of output data representative of the electromagnetic, thermal and electrical power transmission behavior of said first receiving element, - to determine, from said output data set, a set of manufacturing parameters for said second receiving element, - export said set of manufacturing parameters for the manufacture of said second receiving element.

[0011] Advantageously, it is possible to design an optimized energy receiving element, that is, one whose mass is reduced while maintaining a performance level at least equivalent to that of a conventional energy receiving element. More specifically, it is possible to determine a set of manufacturing parameters for such an optimized electrical energy receiving element. Furthermore, the design, and consequently the manufacturing, of the energy receiving element is faster compared to design using an empirical approach.

[0012] According to one embodiment, said input data of said input dataset include at least one objective to be achieved and / or at least one constraint to be respected in order to optimize a shape and / or a topology of said second receiving element.

[0013] According to one embodiment, the method further comprises: - over a reference period: to store in memory a plurality of reference input data sets associated with a plurality of reference output data sets, - during a learning phase: train a machine learning module to associate, for each reference input data set, a reference output data set to obtain an output data prediction model for manufacturing assistance for said second receiving element, - following the learning phase, during a period of use of said prediction model, predict, by the machine learning module, a new output data set representative of an electromagnetic, thermal and electrical power transmission behavior of said first receiving element.

[0014] According to one embodiment, said input data of said input dataset further comprise one or both or a combination of the following features: - at least one predetermined geometry characteristic representative of a predetermined geometry of the first receiving element, - at least one material characteristic representative of electromagnetic, thermal and / or physical properties of the first receiving element, - at least one electrical property characteristic of the electrical energy transfer system.

[0015] According to one embodiment, said output data of said output dataset further comprise one or more or a combination of the following information: - at least one piece of information representative of an optimized geometry of the second receiving element, - at least one piece of information representative of the electromagnetic behavior of said first receiving element, - at least an electrical power transmitted by the first receiving element and / or an electrical power transmission efficiency of the first receiving element.

[0016] Also proposed here is a method for manufacturing an electrical energy receiving element, hereinafter referred to as the second receiving element, configured to cooperate with an electrical energy emitting element such that the second receiving element and the electrical energy emitting element form an electrical energy transfer system designed to allow the transfer of electrical energy in the form of a magnetic field from the electrical energy emitting element to the second receiving element. This manufacturing method comprises: - manufacture said electrical energy receiving element from a set of manufacturing parameters determined by means of a manufacturing assistance process as described above.

[0017] Also proposed herein is a manufacturing assistance system for an electrical energy receiving element, hereinafter referred to as the second receiving element, configured to cooperate with an electrical energy emitting element such that the second receiving element and the electrical energy emitting element form an electrical energy transfer system designed to allow the transfer of electrical energy in the form of a magnetic field from the electrical energy emitting element to the second receiving element, said manufacturing assistance system comprising electronic circuitry configured to: - to obtain a representative set of input data for the characteristics of a reference electrical energy receiving element, hereinafter referred to as the first receiving element, and a predetermined overall temperature of said first receiving element, - determine an initial distribution of copper-iron losses relative to said first receiving element, based on said input data set and said predetermined global temperature, - to perform an iterative optimization of a temperature distribution and update the copper-iron loss distribution from this temperature distribution until their respective values ​​stabilize, - to determine, from the copper-iron loss distribution and the temperature distribution after optimization, a set of output data representative of the electromagnetic, thermal and electrical power transmission behavior of said first receiving element, - to determine, from said output data set, a set of manufacturing parameters for said second receiving element, - export said set of manufacturing parameters for the manufacture of said second receiving element.

[0018] A computer program product is also proposed, comprising instructions that cause a processor to execute the process described above in any of its embodiments when said instructions are executed by the processor. A storage medium for storing such instructions is also proposed. Brief description of the drawings

[0019] The features of the invention mentioned above, as well as others, will become clearer upon reading the following description of at least one exemplary embodiment, said description being made in relation to the accompanying drawings, among which:

[0020] [Fig-1] schematically illustrates a front view of an example of a system of wireless electrical energy transfer;

[0021] [Fig.2] illustrates in diagram form a method of assisting in the manufacture of an electrical energy receiving element, carried out by a system for assisting in the manufacture of the electrical energy receiving element, according to an embodiment;

[0022] [Fig.3] schematically illustrates an example of a multiphysics simulation module for the manufacturing assistance system of the electrical energy receiving element, according to one embodiment;

[0023] [Fig.4] schematically illustrates an example of a hardware platform adapted to implement the manufacturing assistance system for the electrical energy receiving element, according to one embodiment.

[0024] DETAILED DESCRIPTION OF IMPROVEMENTS

[0025] Figure 2 illustrates in diagram form a method for assisting in the manufacture of the electrical energy receiving element ER, carried out by a manufacturing assistance system, noted SYS, of this electrical energy receiving element ER (also referred to hereafter as "second receiving element ER"), according to an embodiment.

[0026] In particular, the manufacturing assistance method described below facilitates the design and subsequent manufacturing of this electrical energy receiver element (ER). Specifically, the manufacturing assistance method described herein allows for the determination of manufacturing parameters (e.g., dimensions, nature of materials, etc.) for such an electrical energy receiver element (ER). The electrical energy receiver element (ER) is then said to be "optimized" in that its total mass is reduced compared to a conventional electrical energy receiver element, while maintaining high levels of electrical power transmitted to the batteries powering the aircraft's landing gear motors, and high efficiency in transmitting this electrical power.

[0027] An example of a hardware platform for implementing the SYS manufacturing assistance system in the form of electronic circuitry is illustrated in [Fig. 4]. This SYS manufacturing assistance system includes, in particular, a multiphysics simulation module, denoted M_S. [Fig. 3] schematically illustrates an example of the M_S multiphysics simulation module of the SYS manufacturing assistance system, according to one embodiment. This M_S multiphysics simulation module includes:

[0028] - an electromagnetic simulation module M_EM,

[0029] - a thermal simulation module M_TH, implementing an algorithm of Computational Fluid Dynamics (CFD)

[0030] - an electrical power simulation module M_PE.

[0031] According to one embodiment, all or part of the manufacturing assistance process described below is implemented in the M_S multiphysics simulation module of the SYS manufacturing assistance system.

[0032] During a step 201, the electromagnetic simulation module M_EM obtains a representative input dataset of characteristics of a "reference" electrical energy receiving element, denoted ERm (also referred to hereafter as the "first receiving element ERm"). This first receiving element ERm is defined by predetermined characteristics. In one example, this input data is transmitted to the electromagnetic simulation module M_EM by a data server and / or sensors and / or by an operator via a human-machine interface, etc.

[0033] More specifically, this input data includes one or both, or a combination of the following characteristics:

[0034] - at least one predetermined geometry feature, denoted GEO, representative of a predetermined geometry of the first receiving element ERm. This predetermined geometry information GEO includes, for example: the predetermined dimensions of the components (e.g., ferromagnetic element 103R, coils 102R...) of the first receiving element ERm (e.g., thickness, width, height, etc.) and a predetermined positioning of these components relative to each other. In addition, this predetermined geometry characteristic GEO includes: the number, length and cross-section of the Litz wires composing the coils 102R as well as the number of turns of the coils 102R of the first receiving element ERm, etc.;

[0035] - at least one characteristic, denoted P_MAT, of the properties of the materials composing the first receiving element ERm (also subsequently called material characteristic P_MAT), representative of the various electromagnetic, thermal and / or physical properties of the components of the first receiving element ERm. These electromagnetic, thermal and / or physical properties are, for example, density, mass, electrical conductivity, thermal conductivity, magnetic permeability, etc. Preferably, the electromagnetic properties of the components of the first receiving element ERm depend on the electrical frequency applied in the electrical energy transfer system 100, the temperature reached by the first receiving element ERm related to the Joule effect and / or the magnetic field induced in the first receiving element ERm;

[0036] - at least one characteristic, denoted P_EL, of the electrical properties of the device electrical energy transfer 100. These electrical properties P_EL are, for example, the effective value ("Root Mean Square" in English) of the intensity of the current passing from the electrical energy emitting element EE to the first receiving element ERm, the frequency of this current, etc.

[0037] It should be noted that this list is not exhaustive and that other characteristics of the first ERm receptor element may be considered as input data.

[0038] According to one embodiment, the input data further include a predetermined global temperature, denoted T°C_G, of the first receiving element ERm. This predetermined global temperature T°C_G corresponds to an assumption made about the temperature reached by the first receiving element ERm when heat is released due to the Joule effect.

[0039] During a step 202, from these input data, including the predetermined overall temperature T°C_G (corresponding to the operating temperature of the energy transfer system 100), the electromagnetic simulation module M_EM determines an initial distribution of copper-iron losses (“EM Lasses”) of the first receiving element ERm. The copper losses, also called load losses (or “short-circuit” losses), correspond to the power released by Joule heating in the electrical circuits of the coils, increased by additional losses (caused by parasitic currents in the windings of (coil in particular). Iron losses, also called no-load losses, correspond to the power expended in the magnetic circuit (by eddy currents, losses occurring within the ferromagnetic core). Copper-iron losses, denoted PEM, are, for example, calculated by the electromagnetic simulation module M_EM using known mathematical formulas, such as Steinmetz's formula. In particular, the iron losses of the ferromagnetic element 103 can be calculated from Steinmetz's formula.

[0040] Then, in step 203, this initial copper-iron loss distribution PEM is transmitted by the electromagnetic simulation module M_EM to the thermal simulation module M_TH. The thermal simulation module M_TH then determines, from the initial copper-iron loss distribution PEM, an initial temperature distribution of the first receiving element ERm. The copper-iron losses PEM (calculated as power per unit volume) are input parameters for determining the temperature of the first receiving element ERm, and in particular, all the electromechanical energy dissipated by the first receiving element ERm is converted into a temperature. This initial temperature distribution, denoted DT, is then transmitted by the thermal simulation module M_TH to the electromagnetic simulation module M_EM.A convergence loop is then executed between the electromagnetic simulation module M_EM and the thermal simulation module M_TH.

[0041] Thus, an iterative optimization is performed, and a new copper-iron loss distribution PEM (step 204 of [Fig. 2]), and then a new temperature distribution DT (step 205 of [Fig. 2]), are determined for the next n cycles of the convergence loop (n an integer greater than 0). The convergence loop stops when, during step 206, the copper-iron loss distribution, and the temperature distribution, respectively, have each converged. In other words, when the difference between a current value (i.e., for cycle n) of the copper-iron loss distribution, and the temperature distribution, respectively, and a subsequent value (i.e.If, for the n+F cycle, the copper-iron loss distribution and temperature distribution are below a predetermined threshold SI, S2 respectively, then the convergence loop stops (step 206, result yes) since the respective values ​​of the copper-iron loss distribution and temperature distribution are stabilized. Otherwise, the convergence loop starts a new cycle (step 206, result no).

[0042] In an example, for a cycle n and a cycle n+1 of the convergence loop, when: (PEM^-PEM,,) PEM„ <S\

[0043] and

[0044] (DTml-DTn) DT„ <S2

[0045] then the convergence loop stops (step 206, result yes), and the value of the copper-iron PEM loss distribution, respectively of the temperature distribution DT, of the last cycle of the convergence loop (eg, cycle n+F) are considered as the final values ​​of the copper-iron PEM loss distribution, respectively of the temperature distribution DT.

[0046] By “distribution” is meant the value for each point of the first receiving element ERm of the copper-iron losses, respectively of temperature.

[0047] It should be noted that other electromagnetic properties of the first receiving element ERm are also determined during the execution of the convergence loop such as magnetic permeability, and more generally all temperature-dependent electromagnetic properties.

[0048] During a step 207, the electromagnetic simulation module M_EM determines, from the final copper-iron loss distribution PEM and the final temperature distribution, denoted T°Cf, : - a final magnetic field at every point of the first receiving element ERm,

[0049] - the self and mutual inductances of the coils 102R and 102E of the first element receiver ERm and electrical energy emitting element EE, - the coupling coefficient.

[0050] In one embodiment, the electrical power simulation module M_PE determines, from: the self and mutual inductances of the coils 102R, 102E of the first receiving element ERm and the electrical energy transmitting element EE, the coupling coefficient and the electrical property information P_EL of the electrical energy transfer system 100, an electrical power information, denoted C_P. This electrical power information C_P includes: an electrical power transmitted from the first receiving element ERm to the batteries of the electric motors of the aircraft's landing gear and / or a transmission efficiency of this electrical power.

[0051] Thus, during this step 207, the multiphysics simulation module M_S, via the electromagnetic simulation module M_EM, the thermal simulation module M_TH and the electrical power simulation module M_PE, is able to determine a set of output data representative of the electromagnetic, thermal and electrical power transmission behavior of the first receiving element ERm and comprising one or more or a combination of the following information: - from the thermal simulation module M_TH: the final temperature distribution T°Cf, - from the electromagnetic simulation module M_EM: at least one piece of information representative of an electromagnetic behavior, noted C_EM of the model electrical energy receiving element ERm such as: the final magnetic field and / or the final copper-iron loss distribution and / or the self and mutual inductances of the coils 102R, 102E of the first receiving element ERm and of the electrical energy emitting element EE and / or the coupling coefficient; - from the electrical power simulation module M_PE: electrical power information C_P such as: the electrical power transmitted and / or the transmission efficiency of this electrical power.

[0052] It should be noted that this list is not exhaustive and that other information may be considered as output data. For example, output data may also include one or a combination of the following information: - the power density transmitted per unit mass (in W / kg), - the mechanical resistance of the components of the model ERm electrical energy receiving element, etc.

[0053] During a step 208, these output data, representative of the electromagnetic, thermal and electrical power transmission behavior of the first receiving element ERm, are used to determine a set of manufacturing parameters (e.g., dimension, material, shape, topology...) of the second receiving element ER.

[0054] These manufacturing parameters are then exported (e.g., as a digital file or display on a human-machine interface) to a human-machine interface of the SYS manufacturing assistance system, or a manufacturing device for the second ER receiver element, for example, for the manufacturing of this second ER receiver element.

[0055] In a particular embodiment, the manufacturing assistance process as described herein, implemented in the M_S multiphysics simulation module of the SYS manufacturing assistance system, is used to identify so-called "key" parameters. These key parameters correspond to a certain type of input data for the SYS manufacturing assistance system that will have a greater influence than other types of input data on the output data having a "physical" impact (i.e., on the shape and / or topology) on the second receiving element ER. This output data includes, for example: the final temperature distribution T°Cf, the final magnetic field at the level of the second receiving element ERm, the final copper-iron loss distribution, the total mass of the first receiving element ERm and its various components, and the coupling coefficient (i.e., efficiency). power transmission), mechanical resistance (in the case where mechanical properties of the first receiving element ERm are studied), etc.

[0056] For this purpose, different input data sets comprising different combinations of input data as described above and different values ​​for these input data are provided to the SYS manufacturing assistance system for the execution of the manufacturing assistance process as described herein.

[0057] The output data having a "physical" impact provided by the SYS manufacturing assistance system are then correlated with the input data to identify among the input data those which make it possible to obtain the second lightest and most efficient ER receiving element in terms of transmitted electrical power.

[0058] These "key" parameters are, for example, the predetermined geometry characteristics GEO (e.g., thickness of the ferromagnetic element 103, dimension of a central hole of the ferromagnetic element 103, etc.). It is thus possible to vary, within predetermined limits, the predetermined geometry characteristics GEO of the second receiving element ERm, in order to design and then manufacture the second receiving element ER.

[0059] In one embodiment, in order to limit the number of input data points to be correlated with the output data having a "physical" impact on the second receiving element ER, certain input data are not used as input to the manufacturing assistance system SYS. In particular, the material characteristics P_MAT and the electrical property characteristics P_EL of the electrical energy transfer device 100 (e.g., frequency and current intensity) are not used, as they are not likely to be adapted during the design and subsequent manufacturing of the second receiving element ER.

[0060] In a particular embodiment, in order to reduce the total mass of the second ER receiving element, while maintaining performance, particularly in terms of high transmitted power, the shape and / or topology of the second ER receiving element are optimized.

[0061] In particular, with regard to topology optimization, it is possible to find the optimal mass distribution while meeting the total mass and performance constraints. Unlike shape optimization, which varies the boundary of the second receiving element ER, topology optimization allows, for example, that material is only present in the "necessary" locations within the ferromagnetic element 103R.

[0062] For this purpose, the input data of the SYS manufacturing assistance system includes one or more objectives to be achieved, such as: an objective of minimization of the total mass of the second receiving element ER, and / or an objective of maximizing the efficiency of electrical power transmission.

[0063] Alternatively, or additionally, the input data includes one or more constraints to be respected for the design, and then manufacture, of the second receiving element ER, such as for example: - a temperature released by the Joule effect below a predetermined threshold (denoted TseuU), and / or - a magnetic field below a predetermined threshold (in teslas, denoted Bseuii) at a given distance (in meters), and / or, - a coupling coefficient greater than a predetermined threshold (denoted kseuU), and / or, - a transmitted power less than a predetermined threshold (denoted Pseuii), and / or,

[0064] - a total mass of the second receiving element ER or of the ferromagnetic element 103R less than a predetermined threshold (noted Mseuii).

[0065] Thus, according to this embodiment, the output data includes at least one characteristic representing a so-called "optimized" geometry of the second receiving element ER, that is to say, one which fulfills the specified objectives while respecting the specified constraints.

[0066] This allows for the direct acquisition, as output data, of an optimal shape and / or topology of the second receiving element ER that fulfills a predefined objective. This objective is to minimize the total mass of the second receiving element ER while ensuring that a high level of electrical power is transmitted and that the energy transfer system 100 is functional (e.g., by ensuring that the overall temperature of the energy transfer system 100 is not too high). It is thus possible to export (e.g., as a digital file or for display on a human-machine interface) this output data, and in particular the representative characteristics of the optimized geometry of the second receiving element ER, to a human-machine interface of the manufacturing assistance system SYS, or to a manufacturing device for the second receiving element ER, for example.

[0067] In a particular embodiment, the SYS manufacturing assistance system further includes a machine learning module denoted M_DL.

[0068] Alternatively, the M_DL machine learning module is located in peripheral equipment to the SYS manufacturing assistance system.

[0069] During a learning phase, the M_DL machine learning module is trained to associate a reference input dataset with a reference output dataset. Thus, for a plurality of reference input datasets, the M_DL machine learning module is trained, for example in a supervised manner, to associate each reference input dataset with a reference output dataset. Reference output data. These reference input data sets and reference output data sets are obtained, for example, after the execution, over a reference period, of all or part of the manufacturing assistance process described herein. More specifically, during the reference period, a plurality of reference input data sets associated with a plurality of reference output data sets are recorded, for example, in a memory of the SYS manufacturing assistance system.

[0070] Alternatively, these reference input datasets associated with these reference output datasets are stored on a server which the SYS manufacturing assistance system and the M_DL machine learning module have access to.

[0071] At the end of the learning phase, a model for predicting output data to assist in the manufacturing of the second ER receiver element is obtained. This prediction model is then implemented in the M_DL machine learning module during a phase of using this prediction model.

[0072] During this period of use of said prediction model, the machine learning module M_DL predicts a new output dataset from a new input dataset.

[0073] In a particular embodiment, the input data is limited in order to predict output data corresponding only to output data that must be optimized (e.g., a characteristic representative of an optimized geometry). Input data such as the material characteristics P_MAT will not be used because they are fixed by a material used in the design and subsequent manufacture of the second receiving element ER.

[0074] The use of such a prediction model makes it possible to reduce the computation time for the design, and then the manufacture, of the second ER receiving element.

[0075] In one embodiment, the output data obtained from specific input data, using the prediction model implemented in the M_DL machine learning module, are compared to the output data obtained from the same specific input data, but using all or part of the manufacturing assistance process described herein. This makes it possible to verify the accuracy of the output data obtained using the prediction model.

[0076] Thus, the manufacturing assistance method as described above (i.e., with or without the use of the prediction model as described here) makes it possible to implement a manufacturing method for the second receiving element ER. In particular, thanks to the output data obtained via the manufacturing assistance method as described here, it is possible to determine a set of manufacturing parameters for this second receiving element ER. This second receiving element ER is then a receiving element energy having a minimized total mass for a high level of power and electrical power transmission efficiency.

[0077] In one example, the manufacturing parameters correspond to the representative characteristics of the optimized geometry of the second ER receiving element included in the output data.

[0078] Fig. 4 schematically illustrates an example of a hardware platform enabling the implementation, in the form of electronic circuitry, of the SYS manufacturing assistance system.

[0079] The hardware platform comprises, connected by a communication bus 410: a processor or CPU (Central Processing Unit) 401; a RAM (Random-Access Memory) 402; a read-only memory 403, for example of the ROM (Read Only Memory) or EEPROM (Electrically-Erasable Programmable ROM) type, such as a Flash memory; a storage unit, such as a HDD (Hard Disk Drive) 404, or a storage media reader, such as an SD (Secure Digital) card reader; and an interface manager Vf 405.

[0080] The I / F 405 interface manager allows the SYS manufacturing assistance system to interact with peripherals, such as human-machine interface devices (input, display of simulation results, etc.) and / or with a communication network and / or other equipment, such as sensors, a manufacturing device for the electrical energy receiving element ER, etc.

[0081] The SYS manufacturing assistance system further comprises the M_S multiphysics simulation module, which includes:

[0082] - the electromagnetic simulation module M_EM,

[0083] - the M_TH thermal simulation module,

[0084] - the electrical power simulation module M_PE.

[0085] The electromagnetic simulation module M_EM, the thermal simulation module M_TH and the electrical power module M_PE are configured to execute all or part of the manufacturing assistance process steps described herein.

[0086] It should also be noted that the term "module" can refer to a software component as well as a hardware component or a set of hardware and software components, a software component itself corresponding to one or more computer programs or subprograms or more generally to any element of a program capable of implementing a function or a set of functions.

[0087] In a particular embodiment, the SYS manufacturing assistance system further includes the M_DL machine learning module.

[0088] The processor 401 is capable of executing instructions loaded into RAM 402 from ROM 403, external memory, a storage medium (such as an SD card), or a communication network. When the hardware platform is powered on, the processor 401 is capable of reading instructions from RAM 402 and executing them. These instructions form a computer program causing the processor 401 to implement all or part of the steps, processes, and operations described herein.

[0089] All or part of the steps, processes, and operations described herein can thus be implemented in software form by the execution of a set of instructions by a programmable machine, for example, a DSP (Digital Signal Processor) or a microcontroller, or be implemented in hardware form by a dedicated machine or electronic component (chip) or a dedicated set of electronic components (chipset), for example, an FPGA (Field Programmable Gate Array) or ASIC (Application-Specific Integrated Circuit). Generally speaking, the SYS manufacturing assistance system includes electronic circuitry adapted and configured to implement the operations, processes, and steps described herein.

Claims

Demands

1. A method for assisting in the manufacture of an electrical energy receiving element (ER), hereinafter referred to as the second receiving element (ER), configured to cooperate with an electrical energy emitting element (EE) such that the second receiving element (ER) and the electrical energy emitting element (EE) form an electrical energy transfer system (100) designed to allow the transfer of electrical energy in the form of a magnetic field from the electrical energy emitting element (EE) to the second receiving element (ER), said method being implemented by a manufacturing assistance system (SYS) in the form of electronic circuitry, said method comprising: - obtaining (201) a representative input data set of characteristics of a reference electrical energy receiving element (ERm), hereinafter referred to as the first receiving element, and a predetermined overall temperature (T°C_G) of said first receiving element (ERm),- determine (202) an initial copper-iron loss distribution (PEM) relative to said first receiving element (ERm), from said input data set and said predetermined global temperature (T°C_G), - perform (204, 205, 206) an iterative optimization of a temperature distribution (DT) and update the copper-iron loss distribution (PEM) from said temperature distribution (DT), until their respective values ​​stabilize, - determine, (207) from the copper-iron loss distribution (PEM) and the temperature distribution (DT) after optimization, an output data set representative of the electromagnetic, thermal and electrical power transmission behavior of said first receiving element (ERm), - determine (208) from said output data set a set of manufacturing parameters of said second receiving element (ER),- export (208) said set of manufacturing parameters for a manufacture of said second receiving element (RE).

2. A method according to claim 1, wherein said input data of said input dataset comprise at least one objective to be achieved and / or at least one constraint to be respected so to optimize a shape and / or topology of said second receiving element (RE).

3. A method according to any one of claims 1 and 2, further comprising: - over a reference period: storing in memory a plurality of reference input data sets associated with a plurality of reference output data sets, - during a learning phase: training a machine learning module (M_DL) to associate, for each reference input data set, a reference output data set to obtain an output data prediction model for manufacturing assistance for said second receiving element (ERm), - following the learning phase, during a period of use of said prediction model, predicting, by the machine learning module (M_DL), a new output data set representative of an electromagnetic, thermal and electrical power transmission behavior of said first receiving element (ERm).

4. A method according to any one of claims 1 to 3, wherein said input data of said input data set further comprise one or a combination of the following features: - at least one predetermined geometry feature (GEO) representative of a predetermined geometry of the first receiving element (ERm), - at least one material feature (P_MAT) representative of electromagnetic, thermal and / or physical properties of the first receiving element (ERm), - at least one electrical properties feature (P_EL) of the electrical energy transfer system (100).

5. A method according to any one of claims 2 to 4, wherein said output data of said output dataset further comprise one or a combination of the following information: - at least one piece of information representative of an optimized geometry of the second receiving element (RE), - at least one piece of information representative of an electromagnetic behavior (C_EM) of said first receiving element (ERm), - at least one electrical power transmitted by the first receiving element (ERm) and / or an electrical power transmission efficiency of the first receiving element (ERm).

6. A method for manufacturing an electrical energy receiving element (ER), hereinafter referred to as the second receiving element (ER), configured to cooperate with an electrical energy emitting element (EE) such that the second receiving element (ER) and the electrical energy emitting element (EE) form an electrical energy transfer system (100) designed to allow the transfer of electrical energy in the form of a magnetic field from the electrical energy emitting element (EE) to the second receiving element (ER), said manufacturing method comprising: - manufacturing said electrical energy receiving element (ER) from a set of manufacturing parameters determined by means of a manufacturing assistance method according to any one of claims 1 to 5.

7. A manufacturing assistance system for an electrical energy receiving element (ER), hereinafter referred to as the second receiving element (ER), configured to cooperate with an electrical energy emitting element (EE) such that the second receiving element (ER) and the electrical energy emitting element (EE) form an electrical energy transfer system (100) designed to allow the transfer of electrical energy in the form of a magnetic field from the electrical energy emitting element (EE) to the second receiving element (ER), said manufacturing assistance system comprising electronic circuitry configured to: - obtain a representative input data set of characteristics of a reference electrical energy receiving element (ERm), hereinafter referred to as the first receiving element, and a predetermined overall temperature (T°C_G) of said first receiving element (ERm),- determine an initial copper-iron loss distribution (PEM) relative to said first receiving element (ERm), from said input data set and said predetermined global temperature (T°C_G), - to perform an iterative optimization of a temperature distribution (DT) and update the copper-iron loss distribution (PEM) from said temperature distribution (DT), until their respective values ​​stabilize, - to determine, from the copper-iron loss distribution (PEM) and the temperature distribution (DT) after optimization, a set of output data representative of an electromagnetic, thermal and electrical power transmission behavior of said first receiving element (ERm), - to determine from said set of output data a set of manufacturing parameters of said second receiving element (ER), - to export said set of manufacturing parameters for a manufacturing of said second receiving element (ER).

8. Product computer program, comprising instructions causing a processor to execute the method according to any one of claims 1 to 5, when said instructions are executed by the processor.

9. Storage medium, storing a computer program comprising instructions causing a processor to execute the method according to any one of claims 1 to 5, when said instructions are read and executed by the processor.

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