Vehicle-mounted multi-mode coupling adaptive wireless charging system

Abstract

The invention relates to the technical field of wireless charging, and discloses a vehicle-mounted multi-mode coupling adaptive wireless charging system, which comprises a system modeling module, a real-time parameter identification module, an optimization problem construction module, an optimal excitation solving module and a driving waveform synthesis module. A vehicle-mounted multi-mode coupling self-adaptive wireless charging method comprises the following steps: identifying a system model in real time through detection and response, constructing and solving an optimization problem which aims at minimizing total input power and meets multiple constraints, obtaining an optimal excitation vector, and synthesizing a driving waveform according to the optimal excitation vector to realize efficient and self-adaptive wireless charging. According to the method, the coupling state is sensed in real time, and the global optimization problem with the minimum total input power as the target is constructed and solved. According to the method, multi-device charging requirements and receiving and transmitting safety constraints are considered, and efficient, safe and self-adaptive multi-target parallel wireless charging is realized by cooperatively controlling the transmitting coil.

Description

Technical Field

[0001] The present invention relates to the technical field of wireless charging, and particularly to a vehicle-mounted multi-modal coupled adaptive wireless charging system. Background Art

[0002] With the rapid development of the new energy vehicle industry, vehicle-mounted wireless charging technology has shown broad application prospects with its advantages of no need for plugging and unplugging, safety and convenience, and has become one of the key technologies to improve the user experience. However, in actual application scenarios, the performance of the wireless charging system highly depends on the electromagnetic coupling state between the ground transmitting coil and the vehicle-mounted receiving coil. The daily parking of vehicles is difficult to ensure ideal alignment between the transmitting and receiving coils. Any lateral, longitudinal or angular offset will cause changes in the system coupling parameters, which is the core challenge faced by current wireless charging technology.

[0003] Most of the existing charging systems are designed and controlled based on fixed and idealized coupling parameters. When the actual coupling state deviates from the preset value due to parking misalignment, the impedance matching relationship of the system is damaged, often resulting in a sharp drop in the energy transfer efficiency or even charging interruption. To improve the tolerance to position offset, some solutions use a multi-coil transmitting array, but its control strategy is usually relatively simple, such as only activating the coil with the strongest signal or using a preset excitation mode. This local or preset control method ignores the complex cross-coupling effects inside the system and is difficult to find the optimal operating point of the whole system, resulting in unnecessary energy loss.

[0004] In addition, in the face of complex scenarios where multiple receiving devices are charged simultaneously, it is more difficult for the existing technology to achieve accurate and efficient allocation of the target power of each device, and it is also unable to fully consider the safe operating boundaries of all electrical nodes (including the transmitting end and the receiving end) in the system during control, presenting certain potential safety hazards.

[0005] Therefore, the present invention proposes a vehicle-mounted multi-modal coupled adaptive wireless charging system to solve the deficiencies of the existing technology. Summary of the Invention

[0006] Aiming at the deficiencies of the existing technology, the present invention provides a vehicle-mounted multi-modal coupled adaptive wireless charging system, which solves the problems of low charging efficiency and poor adaptability caused by the lack of real-time perception of the system coupling state and global optimization control ability in vehicle-mounted wireless charging technology when facing complex working conditions such as dynamic changes in coil positions or multi-target charging.

[0007] To achieve the above objectives, the present invention is realized through the following technical solutions: A vehicle-mounted multi-modal coupled adaptive wireless charging system, the system includes the following modules: A system modeling module for pre - establishing a system state - space model used to describe the electrical characteristics between the transmitting coil and the receiving device within the system; A real - time parameter identification module for controlling the transmitting coil to emit a detection signal, receiving response data, and then identifying and generating a real - time system state model characterizing the current physical state of the system according to the response data and the structure of the system state - space model; An optimization problem construction module for constructing an optimization problem aiming at minimizing the total system input power based on the real - time system state model and combining the target charging power of the receiving device and a preset safety threshold; An optimal excitation solving module for solving the optimization problem via an optimization solver to obtain an optimal excitation vector for driving the transmitting coil; A driving waveform synthesis module for controlling the transmitting coil to generate a driving waveform according to the optimal excitation vector for wireless charging of the receiving device.

[0008] Preferably, the system state - space model in the system modeling module is a global impedance matrix, and the global impedance matrix is used to describe the self - impedance of the transmitting coil and the receiving device coil within the system and the mutual impedance between the coils.

[0009] Preferably, the global impedance matrix includes: A transmitting terminal matrix used to describe the internal coupling relationship of the transmitting coil; A receiving terminal matrix used to describe the internal coupling relationship of the receiving device coil; A transfer impedance matrix used to describe the coupling relationship between the transmitting coil and the receiving device coil.

[0010] Preferably, when controlling the transmitting coil to emit a detection signal, the real - time parameter identification module is specifically used to control the transmitting coil to emit the detection signal in a time - division manner or a code - division manner; The response data received by the real - time parameter identification module is the induced voltage response of the receiving device to the detection signal.

[0011] Preferably, when identifying and generating the real - time system state model, the real - time parameter identification module is specifically used to: Taking the detection signal and the induced voltage response as inputs, using the least - squares method or the Kalman filtering algorithm to solve the time - varying parameters in the system state - space model, thereby generating the real - time system state model.

[0012] Preferably, the optimization problem constructed by the optimization problem construction module is a quadratic - constraint quadratic - programming problem.

[0013] Preferably, the preset safety threshold adopted for the quadratic constrained quadratic programming problem specifically includes: The hardware constraint at the transmitting end for limiting the driving voltage and driving current of the transmitting coil; The safety constraint at the receiving end for limiting the induced voltage and induced current of the receiving device.

[0014] Preferably, the optimal excitation vector obtained by the optimal excitation solving module is a complex vector, and the complex vector defines the target amplitude and target phase of the driving waveform for driving the transmitting coil.

[0015] Preferably, the driving waveform synthesizing module includes a multiphase inverter, and the multiphase inverter is used to synthesize and output the driving waveform for the transmitting coil according to the target amplitude and target phase defined by the optimal excitation vector.

[0016] The present invention also provides a vehicle-mounted multimodal coupling adaptive wireless charging method, and the method includes the following steps: S1. Generate and send a detection signal based on a preset system state space model describing the coupling relationship between the transmitting coil and the receiving device; S2. Receive the response data of the detection signal fed back by the receiving device, and identify the real-time parameters of the system state space model according to the response data to obtain a real-time system state model; S3. Based on the real-time system state model and the target charging power of the receiving device, construct an optimization problem with the goal of minimizing the total system input power and satisfying the target charging power and preset safety threshold; S4. Solve the optimization problem to obtain an optimal excitation vector for driving the transmitting coil; S5. Generate a driving waveform according to the optimal excitation vector and perform wireless charging on the receiving device.

[0017] The present invention provides a vehicle-mounted multimodal coupling adaptive wireless charging system. It has the following beneficial effects: 1. The present invention combines active detection with real-time parameter identification to achieve precise dynamic perception of the multimodal coupling relationship in the vehicle-mounted charging system. Compared with the prior art solutions that rely on fixed parameter models or position sensors, the present invention solves the problem that they cannot adapt to the dynamic changes in the position, attitude, and quantity of the receiving device, which may lead to a serious decline or interruption in charging performance.

[0018] 2. By constructing a global optimization problem with the goal of minimizing the total input power of the system, the present invention can coordinately control all transmitting coils and achieve the optimal overall energy conversion efficiency of the system on the premise of satisfying all charging tasks. This is different from the existing technologies that adopt local control strategies or optimize the coil excitations one by one, avoiding the energy waste and efficiency bottlenecks caused by the latter's failure to consider the cross-coupling between coils and global constraints.

[0019] 3. The optimization model of the present invention uniformly solves the electrical parameter safety thresholds of the transmitting end and the receiving end as hard constraints, ensuring that the charging process is always carried out within the safe operating areas of all components of the system. Compared with the existing technologies that adopt passive protection circuits or simple strategies that only consider overcurrent at the transmitting end, the present invention solves the defects that they may cause overvoltage and overcurrent damage to the receiving device under complex coupling conditions, or limit the charging performance due to overly conservative protection strategies.

[0020] 4. The present invention uses a unified system state space model and an optimal excitation solution framework to achieve parallel and coordinated wireless charging for single or multiple different types of receiving devices within the charging area. It changes the existing technology that usually only supports one-to-one charging or simple power distribution for multiple targets, and solves the problems of low charging efficiency and mutual interference between devices in multi-device scenarios, where energy focusing and differential precise power delivery cannot be carried out. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 is the system architecture diagram of the present invention; Figure 2 is the method flow chart of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0022] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0023] Please refer to Figure 1 , the embodiments of the present invention provide a vehicle-mounted multi-modal coupling adaptive wireless charging system, and the system includes the following modules: A system modeling module, configured to pre-establish a system state space model for describing the electrical characteristics between the transmitting coil and the receiving device in the system; In this embodiment, the system modeling module provides a unified and accurate mathematical description framework for the entire adaptive wireless charging system. Through the pre-established system state space model, this module analyzes and controls a complex electromagnetic coupling system including multiple transmitting coils and multiple receiving devices as a multiple-input multiple-output (MIMO) linear system.

[0024] Specifically, in a preferred implementation, the system state space model is constructed as a global complex impedance matrix. The establishment of this matrix is based on Kirchhoff's laws in circuit theory. Under sinusoidal steady-state operating conditions, this model can accurately describe the internal relationship between the complex voltage vectors and complex current vectors of all coils in the system.

[0025] This relationship can be characterized by the following system state equation: ; In the formula: represents the -dimensional complex voltage column vector of all coils in the entire system; represents the -dimensional complex current row vector of all coils in the entire system; represents the -dimensional global complex impedance matrix, characterizing the overall electrical characteristics of the system; is the number of transmitting coils in the system; is the number of receiving devices in the system.

[0026] To more clearly reveal the energy transfer relationship between the transmitting end and the receiving end and the coupling situation inside each part, in a possible implementation, the system state equation can be further expanded into the form of a block matrix: ; In the formula: is the -dimensional transmitting excitation voltage vector, each element of which represents the complex driving voltage applied to the corresponding transmitting coil, and this vector is the direct input variable of the system control; is the -dimensional receiving induced voltage vector, each element of which represents the complex induced voltage generated across the coil of the corresponding receiving device; is the -dimensional transmitting current vector, each element of which represents the complex current flowing through the corresponding transmitting coil; is the -dimensional receiving current vector, each element of which represents the complex current flowing through the corresponding receiving device and its load; is an \(n\)-dimensional transmitting terminal matrix; the diagonal elements of this matrix are the self-impedances of the respective transmitting coils, reflecting the electrical characteristics of the coils themselves; the off-diagonal elements are the mutual impedances between the transmitting coils, accurately quantifying the cross-coupling effect generated by magnetic field interlinkage inside the transmitting end; is an \(m\)-dimensional receiving terminal matrix; similar to the transmitting terminal matrix, the diagonal elements of this matrix are the self-impedances of the respective receiving device coils, and the off-diagonal elements quantify the degree of cross-coupling between different receiving devices, which is particularly significant when the physical positions of multiple receiving devices are close; is an \(n\times m\)-dimensional transmit-receive transfer impedance matrix; the elements of this matrix characterize the reflection impedance effect of the receiving device coil and its load on the transmitting coil, and it is the main channel describing the effective transfer of energy from the transmitting end to the receiving end; is an \(m\times n\)-dimensional receive-transmit transfer impedance matrix; this matrix describes the contribution of the transmitting coil current to the receiving coil voltage. According to the electromagnetic field reciprocity principle, this matrix is the transpose of the matrix, i.e.,

[0027] By establishing the above global impedance matrix model, the originally complex and multi-variable electromagnetic field problem is transformed into a circuit network problem with a clear structure and definite parameters, providing a solid mathematical foundation for subsequent real-time parameter identification and global optimal control.

[0028] A real-time parameter identification module, which is used to control the transmitting coil to emit a detection signal and receive response data, and then identify and generate a real-time system state model characterizing the current physical state of the system according to the response data and the structure of the system state space model; In this embodiment, the core function of the real-time parameter identification module is to transform the static theoretical model established by the system modeling module into a dynamic model that can accurately reflect the instantaneous state of the physical world. This module realizes the real-time perception of the system state through an active "detection-response-identification" closed-loop process.

[0029] Specifically, this module periodically controls the transmitting coil to emit a specially designed and low-power detection signal to the charging area; this is to actively excite the system without performing high-power charging, so as to observe its response to infer its internal state.

[0030] In a possible implementation, to effectively distinguish the contributions from different transmitting coils, the detection signal can be emitted in a time-division manner. In this mode, the real-time parameter identification module will independently energize each transmitting coil in sequence, and when a specific coil is energized, the remaining transmitting coils will remain silent.

[0031] As another preferred implementation, the detection signal can be emitted in a code-division manner. In this mode, all transmitting coils are simultaneously energized by a set of mathematically orthogonal coding signals. Due to the orthogonal characteristics of the coding signals, at the receiving end, through demodulation operations, the responses from each independent transmitting channel can still be separated.

[0032] After the detection signal is emitted, one or more receiving devices located within the charging area will measure the induced voltage response generated across the two ends of their coils due to electromagnetic induction. This response data, specifically complex voltage values containing amplitude and phase information, is then transmitted back to the real-time parameter identification module via wireless communication.

[0033] After this module collects a complete input-output data set, that is, the known detection signal excitations and the collected induced voltage responses, it begins to perform parameter identification calculations. During the detection phase, the load at the receiving device end can be considered an open circuit, and at this time, the system state equation is simplified. The goal of the identification is to solve the system state space model, that is, the time-varying parameters in the global impedance matrix, mainly the transfer impedance matrix and the transmitting terminal submatrix that changes due to the change of the coupling environment of the non-diagonal elements.

[0034] This identification process is mathematically constructed as a problem of solving an overdetermined linear equation system. Taking the th receiving device as an example, the relationship between the open-circuit voltage response measured during the th detection and the currents of each transmitting coil during this detection can be described by the following linear superposition model: ; where: is the open-circuit voltage measured by the th receiving device during the th detection; is the current flowing through the th transmitting coil during the th detection, and this value can be calculated from the applied detection voltage and the known transmitting terminal impedance; is the transfer impedance to be solved, connecting the th transmitting coil and the th receiving device.

[0035] By performing multiple detections (the number of times is greater than the number of parameters to be solved) with different excitation combinations, the real-time parameter identification module can obtain an overdetermined linear equation system.

[0036] To solve the parameters closest to the true values from the actual data with measurement noise, the real-time parameter identification module adopts the least squares algorithm. This algorithm obtains the optimal estimation of the parameters to be solved by minimizing the sum of the squares of the errors between the predicted response and the actual measured response. In scenarios where continuous tracking of the system state is required, the Kalman filter algorithm can also be used. This algorithm can iteratively update and correct the previous estimated value when each new measurement data arrives, and has better dynamic tracking performance and noise suppression ability.

[0037] Through the above identification calculation, the module finally generates a real-time system state model containing all current real-time parameters, that is, a global impedance matrix given real-time data .

[0038] The optimization problem construction module is used to construct an optimization problem with the goal of minimizing the total system input power based on the real-time system state model and in combination with the target charging power of the receiving device and the preset safety threshold; In this embodiment, the function of the optimization problem construction module is to formally translate the physical requirements and safety boundaries of wireless charging into a precisely structured and solvable mathematical optimization problem. This module is the key logical link connecting system state perception and final control execution.

[0039] Specifically, this module uses the real-time system state model generated by the real-time parameter identification module, that is, the real-time global impedance matrix , as its core calculation basis. At the same time, this module receives the target charging power requirements from each receiving device and various preset safety thresholds in the system. Based on these inputs, the module constructs an optimization problem with the minimization of the total system input active power as the objective function.

[0040] In a preferred implementation, this optimization problem is constructed as a Quadratic-Constrained-Quadratic-Program (QCQP) problem. The choice of this problem form is because the objective function (input power) and the core constraint condition (output power) of the system can both be expressed as quadratic functions of the variables to be solved, which can accurately reflect the physical essence of the system.

[0041] The details of the construction of the optimization problem are as follows: Objective function: Minimize the total input power: The total input active power of the system It is the sum of the active power input to all transmitting coils. This objective function aims to ensure that the overall operating efficiency of the system is maximized while meeting all charging tasks. This objective function can be characterized by the following formula: ; Where: is the total input active power of the system; To be solved dimensional emission excitation voltage vector, which is the independent variable of the optimization problem; for dimensional emission current vector; represents the conjugate transpose operation; Represents the real part operation.

[0042] Based on the system state equation, can be indicates that, therefore About A quadratic homogeneous function of .

[0043] Constraints: The optimization problem contains two main types of constraints: power delivery constraints and safe operation constraints.

[0044] Power delivery constraints: Such constraints ensure that each receiving device can accurately obtain the target charging power it needs. A receiving device with an output power of Must be strictly equal to its target charging power This constraint is an equality constraint, and its mathematical expression is: ; Where: For the The output active power of each receiving device; For the The induced voltage of a receiving device; For the The load current of each receiving device; represents the conjugate operation; For the The target charging power preset by the receiving device.

[0045] because and Real-time global impedance matrix Linearly expressed as is a function of , so the power delivery constraint is about The quadratic equality constraint of .

[0046] Preset safety threshold constraints: Such constraints are inequality constraints, which are used to ensure that all electrical parameters of the system operate within the safe range that the hardware can withstand. In a possible implementation, the safety threshold specifically includes the transmitter hardware constraint and the receiver safety constraint.

[0047] The transmitter hardware constraint is used to protect the hardware of the transmitter system, and specifically limits the upper limit of the amplitude of the drive voltage and drive current of each transmitter coil: ; ; In the formula: is the th element of the transmit excitation voltage vector; is the th element of the transmit current vector; is the maximum drive voltage amplitude allowed by the transmit circuit hardware; is the maximum drive current amplitude allowed by the transmit circuit hardware.

[0048] The receiver safety constraint is used to protect the receiving device, and specifically limits the upper limit of the amplitude of the induced voltage and induced current of each receiving device coil: ; ; In the formula: is the induced voltage of the th receiving device; is the load current of the th receiving device; is the maximum voltage amplitude that the th receiving device can withstand; is the maximum current amplitude that the th receiving device can withstand.

[0049] Since all currents and receiver voltages can be expressed as linear functions, all the above safety threshold constraints mathematically appear as quadratic inequality constraints with respect to .

[0050] The optimization problem construction module combines the above objective function and all constraint conditions, and finally forms a complete quadratic constraint quadratic programming problem whose parameters are determined by the real-time state model and external requirements, and transmits it to the subsequent optimal excitation solving module for solution.

[0051] The optimal excitation solving module is used to solve the optimization problem via an optimization solver, so as to obtain an optimal excitation vector for driving the transmitting coil; In this embodiment, the function of the optimal excitation solving module is to receive and solve the quadratic constraint quadratic programming (QCQP) problem generated by the optimization problem construction module, so as to calculate the optimal control instruction for the system.

[0052] Specifically, the input received by this module is a complete optimization problem. The coefficient matrices of the objective function, equality constraints, and inequality constraints of this problem are uniquely determined by the real-time system state model and the externally set target power and safety threshold. The core task of this module is to find a specific solution within the feasible region defined by this constraint set that can minimize the objective function.

[0053] In a possible implementation manner, this module is embedded with an efficient numerical optimization solver. Since the quadratic constraint quadratic programming problem generated by the optimization problem construction module is a convex optimization problem, this ensures that there is a unique global optimal solution to this problem. Therefore, the solver can use standard convex optimization algorithms, such as the interior point method or the sequential quadratic programming method, to efficiently and stably calculate this global optimal solution, avoiding the risk of falling into a local optimum.

[0054] The output obtained after the solver performs the calculation is the solution to the optimization problem, that is, the optimal excitation vector for driving the transmitting coil.

[0055] The optimal excitation vector is a dimensional complex vector, which can be denoted as . This vector is the only optimal control instruction calculated by the system from an infinite number of possible driving methods according to the real-time state and task requirements.

[0056] The physical meaning of this optimal excitation vector is that it precisely defines the specific parameters of the driving waveforms to be generated by the subsequent driving waveform synthesis module and applied to each transmitting coil. Specifically, the th element in this complex vector contains dual information: First, the amplitude of this complex element defines the target amplitude of the AC driving waveform for driving the th transmitting coil.

[0057] Second, the phase angle of this complex element defines the target phase of the AC driving waveform for driving the th transmitting coil relative to the global reference clock.

[0058] By solving to obtain this optimal excitation vector, the system decomposes the complex cooperative charging task into the amplitude and phase control of each transmitting channel independently. This vector contains all the control information required to achieve the overall goals of the system (high efficiency, safety, and meeting requirements), and is output as a direct instruction to the drive waveform synthesis module to guide the generation of the final drive waveform.

[0059] The drive waveform synthesis module is used to control the transmitting coil to generate a drive waveform according to the optimal excitation vector for wireless charging of the receiving device. In this embodiment, the function of the drive waveform synthesis module is to convert the abstract mathematical instructions calculated by the optimal excitation solving module into physical electrical energy that can actually drive the transmitting coil. This module is the final execution end of the entire closed-loop control system.

[0060] Specifically, the input received by this module is the optimal excitation vector output by the optimal excitation solving module. The core task of this module is to generate and output corresponding high-frequency alternating current drive waveforms for each transmitting coil according to the target amplitudes and target phases of each path precisely defined by this vector.

[0061] In a possible implementation manner, the drive waveform synthesis module physically manifests as a multiphase inverter. This inverter includes independent inverter bridge arms, and each bridge arm is specifically responsible for driving a corresponding transmitting coil, thereby realizing the independent control of transmitting channels.

[0062] The working process of this module is as follows: When receiving the optimal excitation vector , the control logic unit of the multiphase inverter first analyzes this vector. For the th complex element in the vector , the control logic unit extracts two key control parameters from it: The target amplitude , whose value is equal to the modulus of this complex element, that is .

[0063] The target phase , whose value is equal to the phase angle of this complex element, that is .

[0064] Subsequently, the control logic unit, based on the groups of target amplitudes and target phases , generates respective pulse width modulation (PWM) control signals for inverter bridge arms.

[0065] Specifically, the duty cycle of the PWM signal of each inverter leg is precisely adjusted so that the amplitude of the fundamental component of its output voltage matches the target amplitude At the same time, the phase delay of the PWM signal of each inverter leg relative to a system-wide synchronous reference clock is precisely controlled so that the phase of the fundamental component of its output voltage is consistent with the target phase to be consistent.

[0066] In this way, the inverter legs of the multiphase inverter work synchronously, and finally synthesize and output high-frequency AC drive waveforms with the same operating frequency but independently controllable amplitudes and phases for each path. These drive waveforms are then applied to the corresponding emission coils.

[0067] These precisely synthesized drive waveforms generate currents with controlled amplitudes and phases in the emission coils, thereby exciting a precisely "shaped" synthetic magnetic field in space. Through coherent superposition, this magnetic field efficiently and accurately focuses energy on the location of one or more receiving devices, while forming low valleys in the energy distribution in other regions, thereby completing the efficient and safe wireless charging of the receiving devices and finally achieving the control objective solved by the optimization problem.

[0068] Please refer to Figure 2 , the present invention also provides a vehicle-mounted multimodal coupling adaptive wireless charging method, and the method includes the following steps: S1. Generate and emit a detection signal based on a preset system state space model that describes the coupling relationship between the emission coil and the receiving device; In this step, the system first calls a pre-established general mathematical model that can describe the self-coupling and mutual-coupling relationships between all the emission coils and the receiving devices inside the system from the electrical level. Based on the structure of this model, the system controls the emission unit to emit a set of low-power and specially designed detection signals. These detection signals can be emitted through time division or code division, etc., to ensure that the excitations emitted from different emission coils can be effectively distinguished. The purpose is to actively excite the charging environment and prepare for subsequent state perception.

[0069] S2. Receive the response data of the detection signal fed back by the receiving device, and identify the real-time parameters of the system state space model according to the response data to obtain a real-time system state model; When the detection signal acts on the receiving device, each receiving device measures the induced voltage response it senses and feeds back this response data to the system via wireless communication. The system correlates these actually measured response data with the known detection signal excitation. By using estimation algorithms such as the least squares method or Kalman filtering, the system can accurately solve the time-varying parameters in the general mathematical model that change due to changes in the device position, attitude, or quantity, thereby generating a real-time system state model that can accurately characterize the current coupled state of the physical world.

[0070] S3. Based on the real-time system state model and the target charging power of the receiving device, construct an optimization problem aiming to minimize the total system input power and satisfying the target charging power and preset safety thresholds; This step transforms the charging task into a formal mathematical optimization problem. This problem takes minimizing the total system input power as the optimization goal, aiming to achieve the highest energy conversion efficiency. At the same time, this problem is imposed with multiple constraint conditions, including equality constraints to ensure that each receiving device can obtain its target charging power, and a series of inequality constraints representing preset safety thresholds to ensure that the voltage and current at the transmitting end and receiving end do not exceed the hardware's bearing capacity. All the calculations of these goals and constraints are based on the real-time system state model obtained in the previous step.

[0071] S4. Solve the optimization problem to obtain the optimal excitation vector for driving the transmitting coil; The system uses a built-in numerical optimization solver to solve the structured optimization problem constructed in the previous step. Due to the mathematical characteristics of this problem, the solver can efficiently find the unique global optimal solution that satisfies all constraint conditions and minimizes the total system input power. The specific form of this solution is a complex vector, that is, the optimal excitation vector, which contains the accurate target amplitude and target phase information required to drive each transmitting coil.

[0072] S5. Generate a driving waveform according to the optimal excitation vector to perform wireless charging on the receiving device; The system sends the calculated optimal excitation vector as the final control instruction to the driving waveform synthesis module. This module accurately synthesizes and outputs multiple high-frequency alternating current driving waveforms according to the specific amplitudes and phases defined for each channel in the vector. These waveforms drive their respective transmitting coils to generate a synthesized magnetic field in space that undergoes energy focusing and shaping, and this magnetic field precisely transfers energy to the target receiving device, thereby achieving efficient and safe adaptive wireless charging.

[0073] Although embodiments of the present invention have been shown and described, it will be understood by those of ordinary skill in the art that various changes, modifications, substitutions and variations can be made to these embodiments without departing from the principles and spirit of the present invention, and the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A vehicle-mounted multimodal coupling adaptive wireless charging system, characterized in that The system includes the following modules: A system modeling module, configured to pre - establish a system state - space model for describing the electrical characteristics between the transmitting coil and the receiving device within the system; A real - time parameter identification module, configured to control the transmitting coil to emit a detection signal, receive response data, and then identify and generate a real - time system state model characterizing the current physical state of the system based on the response data and the structure of the system state - space model; An optimization problem construction module, configured to construct an optimization problem with the goal of minimizing the total system input power based on the real - time system state model and in combination with the target charging power of the receiving device and a preset safety threshold; An optimal excitation solving module, configured to solve the optimization problem via an optimization solver to obtain an optimal excitation vector for driving the transmitting coil; A driving waveform synthesis module, configured to control the transmitting coil to generate a driving waveform for wireless charging of the receiving device according to the optimal excitation vector.

2. The on-vehicle multimodal coupling adaptive wireless charging system according to claim 1, wherein The system state - space model in the system modeling module is a global impedance matrix, and the global impedance matrix is used to describe the self - impedance of the transmitting coil and the receiving device coil within the system and the mutual impedance between the coils.

3. The on-vehicle multi-modal coupled adaptive wireless charging system according to claim 2, wherein The global impedance matrix includes: A transmitting terminal matrix for describing the internal coupling relationship of the transmitting coil; A receiving terminal matrix for describing the internal coupling relationship of the receiving device coil; A transfer impedance matrix for describing the coupling relationship between the transmitting coil and the receiving device coil.

4. The on-vehicle multimodal coupling adaptive wireless charging system according to claim 1, wherein When controlling the transmitting coil to emit a detection signal, the real - time parameter identification module is specifically configured to control the transmitting coil to emit the detection signal in a time - division manner or a code - division manner; The response data received by the real - time parameter identification module is the induced voltage response of the receiving device to the detection signal.

5. The vehicle-mounted multi-modal coupled adaptive wireless charging system according to claim 4, wherein, When identifying and generating the real - time system state model, the real - time parameter identification module is specifically configured to: Using the detection signal and the induced voltage response as inputs, solve the time - varying parameters in the system state - space model by using the least - squares method or the Kalman filtering algorithm, thereby generating the real - time system state model.

6. The on-vehicle multimodal coupling adaptive wireless charging system according to claim 1, wherein The optimization problem constructed by the optimization problem construction module is a quadratic - constrained quadratic - programming problem.

7. The on-vehicle multimodal coupling adaptive wireless charging system according to claim 6, wherein The preset safety threshold used in the quadratic - constrained quadratic - programming problem specifically includes: A transmitting - end hardware constraint for limiting the driving voltage and driving current of the transmitting coil; A receiving - end safety constraint for limiting the induced voltage and induced current of the receiving device.

8. A vehicle-mounted multi-modal coupled adaptive wireless charging system according to claim 1, characterized in that, The optimal excitation vector obtained by the optimal excitation solving module is a complex vector, and the complex vector defines the target amplitude and target phase of the driving waveform for driving the transmitting coil.

9. The on-vehicle multimodal coupling adaptive wireless charging system according to claim 1, wherein The driving waveform synthesis module includes a multiphase inverter, and the multiphase inverter is configured to synthesize and output the driving waveform for the transmitting coil according to the target amplitude and target phase defined by the optimal excitation vector.

10. A vehicle-mounted multimodal coupling adaptive wireless charging method, applied to the system according to any one of claims 1-9, characterized in that, The method includes the following steps: S1. Based on a preset system state - space model describing the coupling relationship between the transmitting coil and the receiving device, generate and emit a detection signal; S2. Receive the response data of the detection signal fed back by the receiving device, and identify the real-time parameters of the system state space model according to the response data to obtain a real-time system state model; S3. Based on the real-time system state model and the target charging power of the receiving device, construct an optimization problem with the goal of minimizing the total system input power and satisfying the target charging power and the preset safety threshold; S4. Solve the optimization problem to obtain the optimal excitation vector for driving the transmitting coil; S5. Generate a driving waveform according to the optimal excitation vector to perform wireless charging on the receiving device.

Images