An adaptive power regulation method and system for a wireless charging system

Abstract

The application provides an adaptive power regulation method and system of a wireless charging system, and belongs to the field of power transmission between AC power grids and DC power grids. A sweep signal is injected into each transmitting coil unit to obtain a reflected impedance, and characteristic parameters of a coupling coefficient, an equivalent load resistance and a mapping energy feedback willingness coefficient are extracted. Real-time temperature and environmental temperature are collected, and are substituted into an electromagnetic thermal coupling model to predict temperature rise and calculate maximum sustainable bearing power. Topology selection variables and power distribution weights are used as optimization variables to solve a system comprehensive performance functional that maximizes system comprehensive transmission efficiency, energy feedback income and minimizes thermal risk. Topology switching and pulse width modulation phase shift angle adjustment are synchronously performed, and rolling optimization is performed at a predetermined time interval. The application improves efficiency, service life and reliability through joint optimization, thermal risk forward-looking constraint, communication-free sensing, V2G flexible switching, bottom protection and synchronous execution.

Description

Technical Field

[0001] This invention belongs to the field of wireless charging technology, and particularly relates to an adaptive power adjustment method and system for a wireless charging system. Background Technology

[0002] Wireless charging technology has been widely used in electric vehicles, portable electronic devices, and implantable medical devices in recent years. Existing power regulation methods for wireless charging systems can be mainly categorized as follows: The first category is a closed-loop control method based on receiver feedback. The receiver sends information such as load power demand and battery state of charge to the transmitter via independent communication links such as Bluetooth, Wi-Fi, or infrared. The transmitter adjusts the inverter's pulse width modulation duty cycle or operating frequency accordingly to regulate the output power. The second category is a load adaptive method based on impedance detection. The transmitter indirectly estimates the load size by detecting changes in the amplitude or phase of the input impedance, and then adjusts the transmission power. The third category is a power allocation method for multi-transmitter coil systems. When multiple transmitter coil units exist, the system activates the corresponding coil unit based on the receiver's position detection results and distributes the total power to each activated coil using a proportional allocation or a weighted allocation strategy based on the coupling coefficient. The fourth category is a thermal management method for wireless charging systems. Temperature sensors are typically installed on the coils or power devices. When the detected temperature exceeds a preset threshold, the system implements derating output or shutdown protection.

[0003] However, the existing technologies still have the following shortcomings: First, the compensation topology is fixed and singular, and the system cannot dynamically select the optimal topology structure according to changes in operating conditions. Furthermore, topology switching and power allocation are independent and executed step-by-step, making it difficult to simultaneously achieve high efficiency and low thermal stress over a wide load range, thus hindering further improvement in the overall transmission efficiency of the system. Second, thermal management adopts a passive response strategy, only implementing derating or shutdown after the temperature exceeds the limit, lacking forward-looking prediction capabilities. It cannot proactively adjust power allocation to balance heat distribution before the temperature rise exceeds the limit, resulting in limited system lifespan and the risk of overheating. Third, receiver status awareness relies on independent communication links such as Bluetooth and Wi-Fi, which are susceptible to interference and disconnection in complex electromagnetic environments. Moreover, in V2G bidirectional energy interaction scenarios, there is a lack of flexible response mechanisms to grid dispatch requirements, making it impossible to dynamically adjust control strategies based on grid status and vehicle feedback. Fourth, power coordination and allocation are difficult in multi-receiver scenarios. Status information from each receiver is difficult to acquire and process uniformly within the same framework, and the system lacks a feasible fallback mechanism under extreme operating conditions, posing a risk of shutdown. Fifth, the asynchronous switching of the compensation topology and the adjustment of the pulse width modulation parameters can easily cause power interruptions and voltage drops during the switching process, affecting the continuity and stability of system operation. Summary of the Invention

[0004] To overcome the aforementioned deficiencies of the prior art, the present invention provides an adaptive power adjustment method and system for a wireless charging system, which solves the problems in the prior art such as efficiency limitations caused by the separation of topology and power distribution, passive and lagging thermal management, reliance on communication links, lack of V2G coordination and no fallback mechanism for extreme operating conditions, and power interruption caused by asynchronous switching.

[0005] To achieve the above objectives, the present invention provides the following technical solution:

[0006] An adaptive power adjustment method for a wireless charging system, the wireless charging system comprising a transmitter matrix consisting of N transmitter coil units and one or more receivers, where N≥2, each transmitter coil unit is configured with a reconfigurable compensation network, the reconfigurable compensation network containing at least two selectable compensation topologies, the method comprising the following steps:

[0007] Step 1: Obtain the reflection impedance characteristic parameters of each transmitting coil unit;

[0008] Step 2: Extract the coupling coefficient between each transmitting coil unit and the receiving end, the equivalent load resistance of the receiving end, and the characteristic parameters of the receiving end from the reflection impedance characteristic parameters; the characteristic parameters are mapped to the energy feedback willingness coefficient of the receiving end;

[0009] Step 3: Collect the real-time temperature and ambient temperature of each transmitting coil unit; based on the real-time temperature and ambient temperature of each transmitting coil unit, as well as the coupling coefficient and equivalent load resistance obtained in Step 2, predict the temperature rise of each transmitting coil unit in the future time period, and calculate the maximum sustainable power carrying capacity of each transmitting coil unit in the time period based on the predicted temperature rise.

[0010] Step 4: Using the compensation topology selection variables and power allocation weights of each transmitting coil unit as optimization variables, solve for the compensation topology selection variables and power allocation weights that maximize the overall system performance functional. Simultaneously, obtain the optimal compensation topology selection variables and optimal power allocation weights for each transmitting coil unit. The sum of the power allocation weights equals 1. The overall system performance functional is positively correlated with the overall system transmission efficiency and negatively correlated with the thermal risk penalty term of each transmitting coil unit. The weights of the overall system transmission efficiency and the thermal risk penalty term in the overall system performance functional are dynamically adjusted according to the magnitude of the energy feedback willingness coefficient.

[0011] Step 5: Based on the solution results of Step 4, control the reconfigurable compensation network of each transmitting coil unit to switch to the compensation topology corresponding to the optimal compensation topology selection variable, and at the same time adjust the output power of each transmitting coil unit according to the optimal power allocation weight;

[0012] Step Six: Repeat steps one through five at predetermined time intervals.

[0013] Preferably, the method for obtaining the reflection impedance characteristic parameters in step one is as follows: inject a sweep frequency signal into each transmitting coil unit to obtain the complex spectrum of the reflection impedance between each transmitting coil unit and the receiving end; the frequency range of the sweep frequency signal is from the preset resonant frequency minus the preset sweep frequency bandwidth to the preset resonant frequency plus the preset sweep frequency bandwidth, and the preset sweep frequency bandwidth is 15% to 25% of the preset resonant frequency.

[0014] Preferably, the method for extracting the coupling coefficient, equivalent load resistance, and characteristic parameters from the reflection impedance characteristic parameters in step two is as follows: the complex spectrum of the reflection impedance is fitted with the impedance frequency response of the preset equivalent circuit model, and the coupling coefficient, equivalent load resistance, and characteristic parameters are separated from the fitted parameters; the characteristic parameter is the offset of the resonant frequency in the complex spectrum of the reflection impedance relative to the preset reference frequency.

[0015] Preferably, the reconfigurable compensation network includes at least two optional compensation topologies, including LCC topology, CLC topology and SS topology; the reconfigurable compensation network is composed of switching elements and multiple compensation capacitors and compensation inductors, and different compensation topologies are switched by controlling the on and off states of the switching elements.

[0016] Preferably, the energy feedback willingness coefficient ranges from 0 to 1 and is calculated and generated by the battery management system of the receiving end based on the battery state of charge and grid dispatch instructions. The receiving end modulates its own bidirectional controllable rectifier inverter unit by switching, and superimposes the state information containing the energy feedback willingness coefficient onto the reflection impedance of the receiving end with low-frequency spectral characteristics.

[0017] Preferably, when the energy feedback willingness coefficient increases, the weight of the overall system transmission efficiency increases and the weight of the thermal risk penalty term decreases; when the energy feedback willingness coefficient decreases, the weight of the overall system transmission efficiency decreases and the weight of the thermal risk penalty term increases; in step five, the switching of the reconfigurable compensation network and the adjustment of the output power are executed synchronously at the start of the same pulse width modulation period.

[0018] Preferably, in the solution process of step four, when the predicted temperature rise of any transmitting coil unit exceeds the preset temperature safety threshold during the time period, the value of the thermal risk penalty term of the transmitting coil unit is increased, which reduces the optimal power allocation weight of the transmitting coil unit, while the optimal power allocation weight of other transmitting coil units is increased accordingly.

[0019] Preferably, in step four, when there is no feasible solution that makes the overall system performance functional achieve the optimal value, the compensation topology of each transmitting coil unit is switched to the preset default topology, and the output is proportionally dated to the maximum sustainable carrying power of each transmitting coil unit; the predetermined time interval in step six is ​​50 milliseconds to 100 milliseconds.

[0020] Preferably, when the real-time temperature of any transmitting coil unit collected in step three exceeds the preset hardware protection temperature threshold, the reconfigurable compensation network of the transmitting coil unit is switched to bypass mode, the power allocation weight of the transmitting coil unit is set to 0, and the removed power allocation weight is allocated to other transmitting coil units; the bypass mode is the mode in which the transmitting coil unit is electrically disconnected from the transmitting end matrix.

[0021] Preferably, an adaptive power adjustment method and system for a wireless charging system includes:

[0022] The transmitter matrix consists of N transmitter coil units, where N≥2. Each transmitter coil unit contains a reconfigurable compensation network, which contains at least two optional compensation topologies.

[0023] The receiving end includes a bidirectional controllable rectifier-inverter unit;

[0024] Impedance acquisition unit, used to acquire the reflection impedance characteristic parameters of each transmitting coil unit;

[0025] The parameter extraction unit is used to extract the coupling coefficient between each transmitting coil unit and the receiving end, the equivalent load resistance of the receiving end, and the characteristic parameters of the receiving end from the reflection impedance characteristic parameters; the characteristic parameters are mapped to the energy feedback willingness coefficient of the receiving end.

[0026] Temperature acquisition unit, used to acquire real-time temperature and ambient temperature of each transmitting coil unit;

[0027] The thermal prediction unit is used to predict the temperature rise of each transmitting coil unit in the future time period based on the real-time temperature of each transmitting coil unit, the ambient temperature, the coupling coefficient, and the equivalent load resistance, and to calculate the maximum sustainable power carried by each transmitting coil unit in the time period.

[0028] The optimization decision unit is used to solve for the compensation topology selection variables and power allocation weights that make the overall system performance functional obtain the optimal value, using the compensation topology selection variables and power allocation weights of each transmitting coil unit as optimization variables, and at the same time obtain the optimal compensation topology selection variables and optimal power allocation weights of each transmitting coil unit.

[0029] An execution control unit is used to control the reconfigurable compensation network of each transmitting coil unit to switch to the corresponding compensation topology according to the optimal compensation topology selection variable, and to adjust the output power of each transmitting coil unit according to the optimal power allocation weight.

[0030] This invention discloses an adaptive power adjustment method for a wireless charging system, along with the system's technical effects and advantages:

[0031] 1. This invention solves the problem by treating the compensation topology selection and power allocation as coupled variables in the same optimization functional, thereby achieving joint optimization of discrete topology variables and continuous power variables. This overcomes the shortcomings of traditional methods where topology switching and power adjustment are independent and executed step by step, enabling the system to maintain optimal efficiency matching over a wide load range and significantly improving the overall transmission efficiency of the system.

[0032] 2. This invention establishes an electromagnetic-thermal coupling transient model to predict the future temperature rise trend of each transmitting coil unit in advance, and directly embeds the thermal risk into the solution process of the system's comprehensive performance functional in the form of a penalty function, making the power allocation decision forward-looking, realizing proactive prediction and early intervention in thermal management, effectively suppressing local overheating, and extending the system's service life.

[0033] 3. This invention obtains the energy feedback willingness coefficient of the receiver by using the complex spectrum of reflection impedance, eliminating the need for an independent communication link. This avoids the problems of Bluetooth, Wi-Fi and other wireless communications being susceptible to interference and unstable connections in complex electromagnetic environments, thus improving the communication reliability and overall robustness of the system under harsh conditions.

[0034] 4. This invention dynamically adjusts the relative magnitudes of the transmission efficiency weight and thermal risk weight in the system's comprehensive performance functional by using the energy feedback willingness coefficient. This enables the wireless charging system to smoothly switch between charging mode and V2G power supply mode according to grid dispatching needs and the electric vehicle battery status, thus achieving flexible support for grid load.

[0035] 5. By incorporating the thermal risk penalty term of each transmitting coil unit into a unified optimization framework, the power allocation weight is automatically adjusted according to the real-time thermal state of each coil during the rolling optimization process. This enables the spontaneous migration of power from coils in high-temperature states to coils in low-temperature states without the need for dedicated migration control logic, thus simplifying the control architecture and enhancing the system's adaptability.

[0036] 6. By setting up a no-solution detection and fallback mechanism, when the optimization problem has no executable solution due to constraint conflicts, the present invention automatically switches to a preset default topology and performs proportional derating output based on the maximum sustainable carrying power of each coil, ensuring that the system can continue to supply power under extreme conditions and avoiding downtime failures caused by the algorithm having no solution.

[0037] 7. This invention can simultaneously identify the state information (including their own independent energy feedback willingness coefficients) of multiple receivers by separating the multi-frequency features of the impedance complex spectrum, and complete the power coordination and allocation of multiple receivers under the same optimization framework, so that the system has the ability to charge multiple types of devices at the same time.

[0038] 8. This invention eliminates the timing deviation between hardware switching and software adjustment by synchronously executing the compensation topology switching and pulse width modulation phase shift angle adjustment at the beginning of the same pulse width modulation cycle, avoids power interruption and voltage drop at the moment of switching, and realizes seamless transition of system operating state. Attached Figure Description

[0039] Figure 1 A schematic diagram of the adaptive power adjustment system of the wireless charging system provided in an embodiment of the present invention;

[0040] Figure 2 A flowchart illustrating the adaptive power adjustment method for a wireless charging system provided in an embodiment of the present invention;

[0041] Figure 3 A schematic diagram of the joint optimization decision-making process for the system's overall performance functional analysis provided in this embodiment of the invention;

[0042] Figure 4 This is a timing diagram illustrating the synchronous execution of reconfigurable compensation network switching and pulse width modulation phase shift angle adjustment, as provided in an embodiment of the present invention. Detailed Implementation

[0043] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0044] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include," "contain," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that includes a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "includes..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes the element.

[0045] refer to Figure 1-4 This invention provides an adaptive power regulation method and system for a wireless charging system. The invention belongs to the field of wireless charging technology, specifically relating to power transmission and energy management between AC and DC power grids. The invention provides an adaptive power regulation method and system for a wireless charging system. The system includes a transmitter matrix composed of N transmitter coil units, a receiver, and a controller. Each transmitter coil unit is configured with a reconfigurable compensation network containing at least two selectable compensation topologies. The method includes: acquiring the reflection impedance characteristic parameters of each transmitter coil unit, extracting characteristic parameters such as coupling coefficient, equivalent load resistance, and the energy feedback willingness coefficient mapped to the receiver; collecting the real-time temperature and ambient temperature of each transmitter coil unit, substituting them into an electromagnetic-thermal coupling transient model to predict future temperature rise and calculate the maximum sustainable power carrying capacity of each transmitter coil unit; using compensation topology selection variables and power allocation weights as optimization variables, solving the system's overall performance functional to obtain the optimal variable combination that maximizes the system's overall transmission efficiency and energy feedback benefits while minimizing thermal risk; synchronously executing reconfigurable compensation network switching and inverter pulse width modulation phase shift angle adjustment based on the solution results, and repeating the above steps at predetermined time intervals to achieve rolling optimization. This invention achieves optimal matching of hardware and software through joint optimization of topology selection and power allocation in the same functional; it enables forward-looking prediction and proactive intervention in thermal management by directly participating in optimization decisions with thermal prediction results in the form of a penalty function; it passively senses the receiver status through reflective impedance without requiring an independent communication link; it supports flexible switching of V2G bidirectional energy interaction by dynamically adjusting efficiency weights and thermal risk weights through energy feedback willingness coefficients; it ensures continuous power supply capability under extreme conditions through no-solution detection and proportional derating fallback mechanism; and it eliminates power interruption and voltage drop at the moment of switching by executing topology switching and pulse width modulation adjustment simultaneously.

[0046] Example 1

[0047] Purpose of implementation:

[0048] The purpose of this embodiment is to provide an adaptive power adjustment method for wireless charging of electric vehicles, to verify the power adjustment effect of the present invention under single receiver, medium power level, and conventional environmental conditions, and to demonstrate the synergistic effect of the system comprehensive performance functional in transmission efficiency optimization and thermal risk suppression.

[0049] Implementation System:

[0050] The adaptive power adjustment system of the wireless charging system used in this embodiment includes a transmitter matrix, a receiver, and a controller.

[0051] The transmitter matrix consists of a 3×3 array of nine transmitter coil units. Each transmitter coil unit includes a transmitter coil, a reconfigurable compensation network, a current sampling module, a voltage sampling module, and a temperature sensor. Each transmitter coil unit operates at a frequency of 85kHz and has a rated power of 3.3kW. The reconfigurable compensation network configured for each transmitter coil unit offers three selectable compensation topologies: SS topology, LCC topology, and CLC topology, with topology switching achieved via relay control.

[0052] The receiver is a single receiving coil mounted on the bottom of the electric vehicle, comprising the receiving coil, a bidirectional controllable rectifier-inverter unit, and a battery management system interface. The bidirectional controllable rectifier-inverter unit at the receiver supports AC-DC conversion and DC-AC conversion.

[0053] The controller is connected to each transmitting coil unit of the transmitter matrix and the receiver. The controller includes an impedance analysis unit, a thermal prediction unit, and an optimization decision unit.

[0054] Implementation steps:

[0055] Step 1: Obtain the reflection impedance characteristic parameters of each transmitting coil unit. The controller injects a sweep frequency signal into each transmitting coil unit through the impedance analysis unit to obtain the complex spectrum of the reflection impedance between each transmitting coil unit and the receiving end. The frequency range of the sweep frequency signal is from the preset resonant frequency minus the preset sweep frequency bandwidth to the preset resonant frequency plus the preset sweep frequency bandwidth, where the preset sweep frequency bandwidth is 20% of the preset resonant frequency. In this embodiment, the preset resonant frequency is 85kHz, and the sweep frequency range is 68kHz to 102kHz.

[0056] Step two involves extracting the coupling coefficient between each transmitting coil unit and the receiver, the equivalent load resistance of the receiver, and the characteristic parameters of the receiver from the reflection impedance characteristic parameters. The controller performs least-squares fitting between the complex spectrum of the reflection impedance and the impedance frequency response of a preset equivalent circuit model, and separates the coupling coefficient between each transmitting coil unit and the receiver, the equivalent load resistance of the receiver, and the characteristic frequency offset from the fitted parameters. The characteristic parameter is the offset of the resonant frequency in the complex spectrum of the reflection impedance relative to a preset reference frequency. The characteristic frequency offset maps to the energy feedback willingness coefficient of the receiver. The battery management system of the receiver calculates and generates the energy feedback willingness coefficient based on the current battery state of charge and the grid dispatch command. In this embodiment, the battery state of charge of the receiver is 60%, the grid dispatch command is a conventional charging mode, and the battery management system calculates an energy feedback willingness coefficient of 0.3. The receiver modulates the bidirectional controllable rectifier-inverter unit by switching, and superimposes the state information containing the energy feedback willingness coefficient onto the reflection impedance of the receiver as a low-frequency spectral feature. The energy feedback willingness coefficient ranges from 0 to 1, with a value of 0 indicating no reverse feedback willingness and a value of 1 indicating the maximum reverse feedback willingness.

[0057] Step 3: Collect the real-time temperature and ambient temperature of each transmitting coil unit. Temperature sensors collect the real-time temperature of each transmitting coil unit and the ambient temperature. In this embodiment, the ambient temperature is 25℃. The thermal prediction unit, based on the real-time temperature of each transmitting coil unit, the ambient temperature, and the coupling coefficient and equivalent load resistance obtained in Step 2, substitutes these values ​​into a preset electromagnetic-thermal coupling transient model to predict the temperature rise curve of each transmitting coil unit within a future time period. In this embodiment, the future time period is 10 seconds. The electromagnetic-thermal coupling transient model includes a copper loss calculation model, a core loss calculation model, and thermodynamic differential equations related to temperature rise. The thermal prediction unit calculates the maximum sustainable power carried by each transmitting coil unit within the predicted temperature rise curve within the future time period. The maximum sustainable power carried is the maximum power value that each transmitting coil unit can continuously carry under the condition that the predicted temperature rise does not exceed a preset temperature safety threshold. In this embodiment, the preset temperature safety threshold is 85℃.

[0058] Step four: Using the compensation topology selection variables and power allocation weights of each transmitting coil unit as optimization variables, solve for the compensation topology selection variables and power allocation weights that maximize the overall system performance functional, and simultaneously obtain the optimal compensation topology selection variables and optimal power allocation weights for each transmitting coil unit. The optimization decision unit uses the compensation topology selection variables (discrete variables, taking values ​​of SS, LCC, or CLC) and power allocation weights of each transmitting coil unit as optimization variables, and solves for the variable combination that maximizes the overall system performance functional within a preset feasible region. The power allocation weights are continuous variables, greater than or equal to 0 and less than or equal to 1, and the sum of all power allocation weights equals 1. The overall system performance functional is positively correlated with the overall system transmission efficiency and negatively correlated with the thermal risk penalty term of each transmitting coil unit, while also being positively correlated with the energy feedback willingness coefficient. Specifically, the overall system performance functional consists of a first term, a second term, and a third term. The first term is the overall system transmission efficiency, which is jointly determined by the compensation topology selection variables and the power allocation weights. The second term is the energy feedback benefit term, which is obtained by multiplying the energy feedback willingness coefficient by a preset grid peak-shaving benefit constant and then by an efficiency weighting coefficient. The third term is the thermal risk penalty term, which is the sum of the thermal risk penalty functions of each transmitting coil unit and then multiplied by a thermal risk weighting coefficient. This term is preceded by a negative sign. When the actual allocated power of a transmitting coil unit is greater than the maximum sustainable carrying power of that transmitting coil unit, the thermal risk penalty function of that transmitting coil unit increases monotonically as the difference between the actual allocated power and the maximum sustainable carrying power increases. The weights of the system comprehensive transmission efficiency and the thermal risk penalty term in the system comprehensive efficiency functional are dynamically adjusted according to the magnitude of the energy feedback willingness coefficient. When the energy feedback willingness coefficient increases, the weight of the system comprehensive transmission efficiency increases and the weight of the thermal risk penalty term decreases; when the energy feedback willingness coefficient decreases, the weight of the system comprehensive transmission efficiency decreases and the weight of the thermal risk penalty term increases. In this embodiment, the energy feedback willingness coefficient is 0.3, the weight of the system comprehensive transmission efficiency is relatively small, and the weight of the thermal risk penalty term is relatively large, with the system focusing on maximizing transmission efficiency and minimizing thermal risk.

[0059] Step five: Based on the solution results from step four, control the reconfigurable compensation network of each transmitting coil unit to switch to the compensation topology corresponding to the optimal compensation topology selection variable. The controller controls the relays in the reconfigurable compensation network of each transmitting coil unit to switch to the optimal compensation topology based on the solution results. Simultaneously, adjust the pulse width modulation (PWM) phase shift angle of the inverter in each transmitting coil unit according to the optimal power allocation weight to regulate the output power of each transmitting coil unit. The switching of the reconfigurable compensation network and the adjustment of the PWM phase shift angle are performed synchronously at the start of the same PWM cycle.

[0060] Step six: Repeat steps one through five at predetermined time intervals. In this embodiment, the predetermined time interval is 100 milliseconds. The controller repeats the above steps at a period of 100 milliseconds to achieve rolling optimization of adaptive power regulation.

[0061] Implementation results:

[0062] In this embodiment, the total system power requirement is 20kW. The optimal topology combination obtained by the optimization decision unit is as follows: the central transmitting coil unit selects the LCC topology, the four corner transmitting coil units select the CLC topology, and the remaining four transmitting coil units select the SS topology. The power allocation weight of each transmitting coil unit varies between 0.06 and 0.18, with higher power allocation to the central coil and lower power allocation to the corner coils. The overall system transmission efficiency reaches 93.2%. The predicted temperature rise of all transmitting coil units does not exceed the safety threshold of 85℃, and the maximum temperature difference is 4.5℃. Throughout the adjustment process, the receiver output voltage remains stable at the rated value, and the power fluctuation is less than ±2%.

[0063] Example 2

[0064] Purpose of implementation:

[0065] The purpose of this embodiment is to provide an adaptive power adjustment method in a scenario where multiple receiving devices are charging simultaneously, to verify the effect of the present invention on multi-target power coordination allocation under conditions of multiple receiving ends, different power levels, and different energy feedback intentions, and to demonstrate the ability of the complex spectrum of reflection impedance in multi-receiver identification and frequency division multiplexing transmission of state information.

[0066] Implementation System:

[0067] The adaptive power adjustment system of the wireless charging system used in this embodiment includes a transmitter matrix, three receivers, and a controller.

[0068] The transmitter matrix consists of 16 transmitter coil units in a 4×4 array. Each transmitter coil unit includes a transmitter coil, a reconfigurable compensation network, a current sampling module, a voltage sampling module, and a temperature sensor. Each transmitter coil unit operates at a frequency of 125kHz, and the reconfigurable compensation network configured for each transmitter coil unit offers two optional compensation topologies: SS topology and LCC topology.

[0069] There are three receivers: a smartphone, a tablet, and a wireless headset. Each receiver includes a receiving coil, a bidirectional controllable rectifier-inverter unit, and a battery management system interface. The smartphone has a rated power of 15W, the tablet has a rated power of 30W, and the wireless headset has a rated power of 5W. The battery management system interface of each receiver is used to output its respective battery state-of-charge information and energy feedback willingness coefficient.

[0070] The controller is connected to each transmitting coil unit and each receiving end of the transmitter matrix. The controller includes an impedance analysis unit, a thermal prediction unit, and an optimization decision unit.

[0071] Implementation steps:

[0072] Step 1: Obtain the reflection impedance characteristic parameters of each transmitting coil unit. The controller injects a sweep frequency signal into each transmitting coil unit through the impedance analysis unit to obtain the complex spectrum of the reflection impedance between each transmitting coil unit and the receiving end. The frequency range of the sweep frequency signal is from the preset resonant frequency minus the preset sweep frequency bandwidth to the preset resonant frequency plus the preset sweep frequency bandwidth, where the preset sweep frequency bandwidth is 20% of the preset resonant frequency. In this embodiment, the preset resonant frequency is 125kHz, and the sweep frequency range is 100kHz to 150kHz.

[0073] Step two involves extracting the coupling coefficient between each transmitting coil unit and the receiver, the equivalent load resistance of the receiver, and the characteristic parameters of the receiver from the reflection impedance characteristic parameters. The controller performs least-squares fitting of the complex spectrum of the reflection impedance with the impedance frequency response of the preset equivalent circuit model. Since there are three receivers, the complex spectrum of the reflection impedance presents three characteristic frequency points, each corresponding to one receiver. The coupling coefficient matrix between each transmitting coil unit and each receiver, the equivalent load resistance of each receiver, and the characteristic frequency offset of each receiver are separated from the fitting parameters. Each characteristic frequency offset maps to the energy feedback willingness coefficient of each receiver. The battery management systems of the three receivers independently calculate their respective energy feedback willingness coefficients. In this embodiment, the smartphone's battery state of charge is 30%, and the energy feedback willingness coefficient is 0.2; the tablet's battery state of charge is 60%, and the energy feedback willingness coefficient is 0.5; the wireless headset's battery state of charge is 85%, and the energy feedback willingness coefficient is 0.8. The three receivers modulate their respective bidirectional controllable rectifier-inverter units at different frequencies, superimposing their respective energy feedback willingness coefficients onto the reflection impedance with low-frequency spectral characteristics at different frequencies. The frequencies of each low-frequency spectral characteristic are all lower than the operating frequency of the wireless charging system, 125kHz.

[0074] Step 3: Collect the real-time temperature and ambient temperature of each transmitting coil unit. Temperature sensors collect the real-time temperature of each transmitting coil unit and the ambient temperature. In this embodiment, the ambient temperature is 22℃. The thermal prediction unit, based on the real-time temperature of each transmitting coil unit, the ambient temperature, and the coupling coefficient matrix and equivalent load resistance obtained in Step 2, substitutes these values ​​into a preset electromagnetic-thermal coupling transient model to predict the temperature rise curve of each transmitting coil unit within a future time period. In this embodiment, the future time period is 5 seconds. The thermal prediction unit calculates the maximum sustainable power carrying capacity of each transmitting coil unit within the predicted temperature rise curve within the future time period.

[0075] Step four: Using the compensation topology selection variables and power allocation weights of each transmitting coil unit as optimization variables, solve for the compensation topology selection variables and power allocation weights that maximize the overall system performance functional (ESF). Simultaneously, obtain the optimal compensation topology selection variables and optimal power allocation weights for each transmitting coil unit. The optimization decision unit uses the compensation topology selection variables (discrete variables, with values ​​of SS or LCC) and power allocation weights of the 16 transmitting coil units as optimization variables, and solves for the variable combination that maximizes the overall system performance functional within a preset feasible region. The sum of the power allocation weights equals 1. The overall system performance functional is positively correlated with the overall system transmission efficiency, negatively correlated with the thermal risk penalty term of each transmitting coil unit, and positively correlated with the sum of energy feedback benefits at each receiver. During the solution process, the power demand constraint of each receiver must be satisfied, i.e., the power allocated to each receiver is equal to its respective rated power demand. The weights of the overall system transmission efficiency and the thermal risk penalty term are dynamically adjusted based on the weighted average of the energy feedback willingness coefficients of each receiver.

[0076] Step five: Based on the solution results from step four, control the reconfigurable compensation network of each transmitting coil unit to switch to the compensation topology corresponding to the optimal compensation topology selection variable. The controller controls the switching elements in the reconfigurable compensation network of each transmitting coil unit to switch to the optimal compensation topology based on the solution results. Simultaneously, adjust the pulse width modulation (PWM) phase shift angle of the inverter in each transmitting coil unit according to the optimal power allocation weight to regulate the output power of each transmitting coil unit. The switching of the reconfigurable compensation network and the adjustment of the PWM phase shift angle are performed synchronously at the start of the same PWM cycle.

[0077] Step six: Repeat steps one through five at predetermined time intervals. In this embodiment, the predetermined time interval is 50 milliseconds, and the controller repeats the above steps at 50-millisecond intervals.

[0078] Implementation results:

[0079] In this embodiment, the total system power requirement is 50W. The optimal topology combination obtained by the optimization decision unit is as follows: the transmitting coil unit strongly coupled with the smartphone is selected from the SS topology, the transmitting coil unit strongly coupled with the tablet is selected from the LCC topology, and the transmitting coil unit strongly coupled with the wireless headset is selected from the SS topology. The power allocation weight of each transmitting coil unit varies between 0.02 and 0.12, and the overall system transmission efficiency reaches 91.8%. The receiving end corresponding to the energy feedback willingness coefficient of the tablet (0.5) and the energy feedback willingness coefficient of the wireless headset (0.8) receives a higher energy feedback benefit weight. The maximum temperature difference of all transmitting coil units is 3.8℃, and the actual received power of the three receiving ends are 14.8W, 29.5W, and 5.0W, respectively, all of which meet the power requirements of each receiving end.

[0080] Example 3

[0081] Purpose of implementation:

[0082] The purpose of this embodiment is to provide an adaptive power regulation method in a V2G (vehicle-to-grid) bidirectional energy interaction scenario, to verify the dynamic adjustment mechanism of efficiency weight and thermal risk weight in the system comprehensive performance functional when the power transmission direction is reversed and the energy feedback willingness coefficient is high, as well as the adaptability of the compensation topology selection to bidirectional power transmission.

[0083] Implementation System:

[0084] The adaptive power adjustment system of the wireless charging system used in this embodiment includes a transmitter matrix, a receiver, and a controller.

[0085] The transmitter matrix consists of four transmitter coil units in a 2×2 array. Each transmitter coil unit includes a transmitter coil, a reconfigurable compensation network, a current sampling module, a voltage sampling module, and a temperature sensor. Each transmitter coil unit operates at a frequency of 85kHz and supports bidirectional power transmission. The reconfigurable compensation network configured for each transmitter coil unit offers two optional compensation topologies: SS topology and LCC topology.

[0086] The receiving end is an electric vehicle and includes a receiving coil, a bidirectional controllable rectifier-inverter unit, and a battery management system interface. The bidirectional controllable rectifier-inverter unit of the receiving end supports AC-DC conversion and DC-AC conversion, that is, it supports both charging mode and power feeding mode simultaneously.

[0087] The controller is connected to each transmitting coil unit and receiver unit of the transmitting matrix. The controller communicates with the power grid dispatch center via wired or wireless means to receive real-time power grid dispatch instructions. The controller includes an impedance analysis unit, a thermal prediction unit, and an optimization decision-making unit.

[0088] Implementation steps:

[0089] Step 1: Obtain the reflection impedance characteristic parameters of each transmitting coil unit. The controller injects a sweep frequency signal into each transmitting coil unit through the impedance analysis unit to obtain the complex spectrum of the reflection impedance between each transmitting coil unit and the receiving end. The frequency range of the sweep frequency signal is from the preset resonant frequency minus the preset sweep frequency bandwidth to the preset resonant frequency plus the preset sweep frequency bandwidth, where the preset sweep frequency bandwidth is 20% of the preset resonant frequency. In this embodiment, the preset resonant frequency is 85kHz, and the sweep frequency range is 68kHz to 102kHz.

[0090] Step two involves extracting the coupling coefficient between each transmitting coil unit and the receiver, the equivalent load resistance of the receiver, and the characteristic parameters of the receiver from the reflection impedance characteristic parameters. The controller performs least-squares fitting of the complex spectrum of the reflection impedance with the impedance frequency response of the preset equivalent circuit model, and separates the coupling coefficient, equivalent load resistance, and characteristic frequency offset from the fitting parameters. The characteristic frequency offset maps to the energy feedback willingness coefficient of the receiver. The battery management system of the receiver calculates and generates the energy feedback willingness coefficient based on the battery state of charge and the grid dispatch command. In this embodiment, the system is initially in charging mode, the grid dispatch command is regular charging, the battery state of charge is 60%, and the battery management system calculates an energy feedback willingness coefficient of 0.3. When the grid dispatch command switches to V2G feeding mode, the battery state of charge is 85%, the grid has peak-shaving demand, and the battery management system recalculates the energy feedback willingness coefficient to 0.9. The receiver modulates the bidirectional controllable rectifier inverter unit by switching, and superimposes the state information containing the energy feedback willingness coefficient onto the reflection impedance of the receiver as a low-frequency spectral feature. When the controller extracts the characteristic frequency offset, it determines the current power transmission direction by judging the sign of the offset. A positive offset indicates charging mode, and a negative offset indicates power feeding mode.

[0091] Step 3: Collect the real-time temperature and ambient temperature of each transmitting coil unit. Temperature sensors collect the real-time temperature of each transmitting coil unit and the ambient temperature. In this embodiment, the ambient temperature is 28℃. The thermal prediction unit, based on the real-time temperature of each transmitting coil unit, the ambient temperature, and the coupling coefficient and equivalent load resistance obtained in Step 2, substitutes these values ​​into a preset electromagnetic-thermal coupling transient model to predict the temperature rise curve of each transmitting coil unit within a future time period. In this embodiment, the future time period is 8 seconds. The thermal prediction unit calculates the maximum sustainable power carrying capacity of each transmitting coil unit within the predicted temperature rise curve within the future time period.

[0092] Step four: Using the compensation topology selection variables and power allocation weights of each transmitting coil unit as optimization variables, solve for the compensation topology selection variables and power allocation weights that maximize the overall system performance functional (ESF). Simultaneously, obtain the optimal compensation topology selection variables and optimal power allocation weights for each transmitting coil unit. The optimization decision unit uses the compensation topology selection variables (discrete variables, with values ​​of SS or LCC) and power allocation weights of the four transmitting coil units as optimization variables to solve for the variable combination that maximizes the overall system performance functional (ESF). The sum of the power allocation weights equals 1. The overall system performance functional is positively correlated with the overall system transmission efficiency and negatively correlated with the thermal risk penalty term of each transmitting coil unit, while also being positively correlated with the energy feedback willingness coefficient. The weights of the overall system transmission efficiency and the thermal risk penalty term are dynamically adjusted according to the magnitude of the energy feedback willingness coefficient. When the energy feedback willingness coefficient increases, the weight of the overall system transmission efficiency increases and the weight of the thermal risk penalty term decreases; conversely, when the energy feedback willingness coefficient decreases, the weight of the overall system transmission efficiency decreases and the weight of the thermal risk penalty term increases. In this embodiment, when the energy feedback willingness coefficient is 0.3, the weight of the overall system transmission efficiency is relatively small, while the weight of the thermal risk penalty term is relatively large, indicating that the system focuses on maximizing charging efficiency and minimizing thermal risk. When the energy feedback willingness coefficient is 0.9, the weight of the overall system transmission efficiency is relatively large, while the weight of the thermal risk penalty term is relatively small, significantly increasing the weight of grid peak-shaving revenue in the overall system performance functional, indicating that the system tends to sacrifice some transmission efficiency in exchange for higher energy feedback revenue.

[0093] Step 5: Based on the solution results from Step 4, control the reconfigurable compensation network of each transmitting coil unit to switch to the compensation topology corresponding to the optimal compensation topology selection variable. The controller controls the reconfigurable compensation network of each transmitting coil unit to switch to the optimal compensation topology based on the solution results. When the energy feedback willingness coefficient is 0.9, the optimization decision unit tends to select the LCC topology that supports bidirectional high-efficiency transmission. Simultaneously, the pulse width modulation phase shift angle of the inverter of each transmitting coil unit is adjusted according to the optimal power allocation weight to regulate the output power of each transmitting coil unit. The switching of the reconfigurable compensation network and the adjustment of the pulse width modulation phase shift angle are performed synchronously at the start of the same pulse width modulation cycle.

[0094] Step six: Repeat steps one through five at predetermined time intervals. In this embodiment, the predetermined time interval is 80 milliseconds, and the controller repeats the above steps at 80-millisecond intervals.

[0095] Implementation results:

[0096] In this embodiment, when the energy feedback willingness coefficient is 0.3, the system is in conventional charging mode, with a comprehensive transmission efficiency of 94.1%. The thermal risk penalty for each transmitting coil unit is strictly constrained, with a maximum temperature rise of 32°C. When the grid dispatch command switches to V2G feeding mode and the energy feedback willingness coefficient becomes 0.9, the optimization decision unit automatically switches the compensation topology of each transmitting coil unit from SS topology to LCC topology, and the power allocation weights are redistributed. The system feeds back 15kW of power to the grid with a transmission efficiency of 92.5%, and the maximum temperature rise of each transmitting coil unit is 41°C (higher than the charging mode but still within the safe threshold of 85°C), significantly increasing the grid peak-shaving benefits. The system switches between the two modes in 120 milliseconds, and the power output is continuous during the switching process without interruption or voltage drop.

[0097] Example 4

[0098] Purpose of implementation:

[0099] The purpose of this embodiment is to provide a method for thermal equalization and power migration of the transmitting unit in a dynamic wireless charging scenario, so as to verify the ability of the present invention to achieve automatic power migration and seamless hot-swappable redundancy exit when the hardware protection is triggered under the dynamic activation and deactivation conditions of the transmitting coil unit.

[0100] Implementation System:

[0101] The adaptive power adjustment system of the wireless charging system used in this embodiment includes a transmitter matrix, a receiver, and a controller.

[0102] The transmitter matrix consists of 10 transmitter coil units arranged sequentially along the road direction. Each transmitter coil unit includes a transmitter coil, a reconfigurable compensation network, a current sampling module, a voltage sampling module, and a temperature sensor. The spacing between adjacent transmitter coil units is 0.5 meters, and each transmitter coil unit has a rated power of 10kW and an operating frequency of 85kHz. The reconfigurable compensation network configured for each transmitter coil unit offers two optional compensation topologies: SS topology and LCC topology.

[0103] The receiving end is a single receiving coil located at the bottom of a moving electric vehicle, and includes the receiving coil and a bidirectional controllable rectifier-inverter unit.

[0104] The controller is connected to each transmitting coil unit of the transmitter matrix and the receiver. The controller includes an impedance analysis unit, a thermal prediction unit, and an optimization decision unit.

[0105] Implementation steps:

[0106] Step 1: Obtain the reflection impedance characteristic parameters of each transmitting coil unit. The controller continuously injects a sweep frequency signal into each transmitting coil unit through the impedance analysis unit to obtain the complex spectrum of the reflection impedance between each transmitting coil unit and the receiving end. The frequency range of the sweep frequency signal is from a preset resonant frequency minus a preset sweep frequency bandwidth to a preset resonant frequency plus a preset sweep frequency bandwidth, where the preset sweep frequency bandwidth is 20% of the preset resonant frequency. In this embodiment, the preset resonant frequency is 85kHz, and the sweep frequency range is 68kHz to 102kHz.

[0107] Step two involves extracting the coupling coefficient between each transmitting coil unit and the receiver, the equivalent load resistance of the receiver, and the characteristic parameters of the receiver from the reflection impedance characteristic parameters. The controller performs least-squares fitting of the complex spectrum of the reflection impedance with the impedance frequency response of a preset equivalent circuit model, and separates the coupling coefficient between each transmitting coil unit and the receiver, the equivalent load resistance of the receiver, and the characteristic frequency offset from the fitted parameters. The characteristic frequency offset maps to the energy feedback willingness coefficient of the receiver. In this embodiment, the electric vehicle is in a driving charging state, and the energy feedback willingness coefficient is 0.1. When the electric vehicle drives over a certain transmitting coil unit, the coupling coefficient between that transmitting coil unit and the receiver increases. The controller monitors the coupling coefficient of each transmitting coil unit in real time, and activates the transmitting coil unit when the coupling coefficient exceeds the activation threshold. As the vehicle moves, typically 2 to 3 transmitting coil units are coupled to the receiver simultaneously.

[0108] Step 3: Collect the real-time temperature and ambient temperature of each transmitting coil unit. Temperature sensors collect the real-time temperature of each transmitting coil unit and the ambient temperature in real time. In this embodiment, the ambient temperature is 30℃. The thermal prediction unit, based on the real-time temperature of each transmitting coil unit, the ambient temperature, and the coupling coefficient and equivalent load resistance obtained in Step 2, substitutes these values ​​into a preset electromagnetic-thermal coupling transient model to predict the temperature rise curve of each transmitting coil unit within a future time period. In this embodiment, the future time period is 10 seconds. The thermal prediction unit calculates the maximum sustainable power carrying capacity of each transmitting coil unit within the predicted temperature rise curve within the future time period.

[0109] Step four: Using the compensation topology selection variables and power allocation weights of each transmitting coil unit as optimization variables, solve for the compensation topology selection variables and power allocation weights that maximize the overall system performance functional, and simultaneously obtain the optimal compensation topology selection variables and optimal power allocation weights for each transmitting coil unit. The optimization decision unit uses the compensation topology selection variables and power allocation weights of the activated transmitting coil units as optimization variables to solve for the variable combination that maximizes the overall system performance functional. The sum of the power allocation weights equals 1. The overall system performance functional is positively correlated with the overall system transmission efficiency and negatively correlated with the thermal risk penalty term of each transmitting coil unit. When the electromagnetic-thermal coupling transient model predicts that the temperature rise of any transmitting coil unit exceeds a preset temperature safety threshold within the future time period, the value of the thermal risk penalty term for that transmitting coil unit increases, causing the optimal power allocation weight of that transmitting coil unit to decrease, while the optimal power allocation weights of other transmitting coil units increase accordingly. In this embodiment, the preset temperature safety threshold is 85℃.

[0110] Step 5: Based on the solution results from Step 4, control the reconfigurable compensation network of each transmitting coil unit to switch to the compensation topology corresponding to the optimal compensation topology selection variable. The controller controls the reconfigurable compensation network of each activated transmitting coil unit to switch to the optimal compensation topology based on the solution results. Simultaneously, adjust the pulse width modulation phase shift angle of the inverter of each transmitting coil unit according to the optimal power allocation weight to adjust the output power of each transmitting coil unit. The switching of the reconfigurable compensation network and the adjustment of the pulse width modulation phase shift angle are performed synchronously at the start of the same pulse width modulation cycle. When the real-time temperature of any transmitting coil unit exceeds the preset hardware protection temperature threshold, the reconfigurable compensation network of that transmitting coil unit is switched to bypass mode, the power allocation weight of that transmitting coil unit is set to 0, and the removed power allocation weight is allocated to other transmitting coil units according to the proportion of the current power allocation weight of each other transmitting coil unit. The bypass mode is the mode in which the transmitting coil unit is electrically disconnected from the transmitting end matrix. In this embodiment, the hardware protection temperature threshold is 90℃.

[0111] Step six: Repeat steps one through five at predetermined time intervals. In this embodiment, the predetermined time interval is 50 milliseconds, and the controller repeats the above steps at 50-millisecond intervals.

[0112] Implementation results:

[0113] In this embodiment, the total system power requirement is 20kW. During the electric vehicle's operation, a certain transmitting coil unit, having operated continuously for over 30 seconds, reaches a temperature of 72°C. The thermal prediction unit predicts that its temperature rise will exceed the safety threshold of 85°C within the next 10 seconds. During the rolling optimization process, the thermal risk penalty term for this transmitting coil unit increases sharply, causing its power allocation weight to automatically decrease from 0.15 to 0.06. Simultaneously, the power allocation weight of adjacent transmitting coil units increases from 0.12 to 0.21, achieving automatic power migration. Throughout the migration process, the receiver power fluctuation is less than ±3%. When the real-time temperature of this transmitting coil unit exceeds the hardware protection temperature threshold of 90°C, the controller switches the transmitting coil unit to bypass mode at the start of the next PWM cycle, forcibly setting its power allocation weight to 0. The removed power weight is redistributed according to the proportion of the current power allocation weight of adjacent transmitting coil units, and the receiver does not perceive a power interruption. The overall system transmission efficiency remains between 91.5% and 93.8% throughout the entire dynamic process.

[0114] Example 5

[0115] Purpose of implementation:

[0116] The purpose of this embodiment is to provide a fallback method under extreme operating conditions, to verify the ability of the present invention to ensure that the system can safely and continuously supply power under any operating condition by switching to a preset default topology and performing proportional derating output when there is no feasible solution to the optimization problem.

[0117] Implementation System:

[0118] The adaptive power adjustment system of the wireless charging system used in this embodiment includes a transmitter matrix, a receiver, and a controller. The system configuration is the same as in Embodiment 1.

[0119] The transmitter matrix consists of a 3×3 array of nine transmitter coil units. Each transmitter coil unit includes a transmitter coil, a reconfigurable compensation network, a current sampling module, a voltage sampling module, and a temperature sensor. Each transmitter coil unit operates at a frequency of 85kHz and has a rated power of 3.3kW. The reconfigurable compensation network configured for each transmitter coil unit offers three selectable compensation topologies: SS topology, LCC topology, and CLC topology.

[0120] The receiver is a single receiving coil installed at the bottom of the electric vehicle, which includes the receiving coil, a bidirectional controllable rectifier-inverter unit, and a battery management system interface.

[0121] The controller is connected to each transmitting coil unit of the transmitter matrix and the receiver. The controller includes an impedance analysis unit, a thermal prediction unit, and an optimization decision unit.

[0122] Implementation steps:

[0123] Step 1: Obtain the reflection impedance characteristic parameters of each transmitting coil unit. The controller injects a sweep frequency signal into each transmitting coil unit through the impedance analysis unit to obtain the complex spectrum of the reflection impedance between each transmitting coil unit and the receiving end. The frequency range of the sweep frequency signal is from the preset resonant frequency minus the preset sweep frequency bandwidth to the preset resonant frequency plus the preset sweep frequency bandwidth, where the preset sweep frequency bandwidth is 20% of the preset resonant frequency. In this embodiment, the preset resonant frequency is 85kHz, and the sweep frequency range is 68kHz to 102kHz.

[0124] Step two involves extracting the coupling coefficient between each transmitting coil unit and the receiver, the equivalent load resistance of the receiver, and the characteristic parameters of the receiver from the reflection impedance characteristic parameters. The controller performs least-squares fitting between the complex spectrum of the reflection impedance and the impedance frequency response of a preset equivalent circuit model, separating the coupling coefficient, equivalent load resistance, and characteristic frequency offset from the fitted parameters. The characteristic frequency offset maps to the energy feedback willingness coefficient of the receiver. In this embodiment, the energy feedback willingness coefficient is 0.2.

[0125] Step 3: Collect the real-time temperature and ambient temperature of each transmitting coil unit. Temperature sensors collect the real-time temperature and ambient temperature of each transmitting coil unit. In this embodiment, the environment is a high-temperature summer environment with an ambient temperature of 45℃. Six of the nine transmitting coil units have exceeded 80℃ due to continuous high power output, and the temperature of the remaining three transmitting coil units has also exceeded 70℃. The thermal prediction unit, based on the real-time temperature of each transmitting coil unit, the ambient temperature, and the coupling coefficient and equivalent load resistance obtained in Step 2, substitutes them into a preset electromagnetic-thermal coupling transient model to predict the temperature rise curve of each transmitting coil unit in the future time period. In this embodiment, the future time period is 10 seconds. The thermal prediction unit calculates the maximum sustainable power carrying capacity of each transmitting coil unit in the future time period based on the predicted temperature rise curve. Since each transmitting coil unit is already in a high-temperature state, the calculated maximum sustainable power carrying capacity is relatively low, approximately 40% to 60% of the rated power of each transmitting coil unit.

[0126] Step four: Using the compensation topology selection variables and power allocation weights of each transmitting coil unit as optimization variables, solve for the compensation topology selection variables and power allocation weights that maximize the overall system performance functional. Simultaneously, obtain the optimal compensation topology selection variables and optimal power allocation weights for each transmitting coil unit. The optimization decision unit uses the compensation topology selection variables (discrete variables, taking values ​​of SS, LCC, or CLC) and power allocation weights of the nine transmitting coil units as optimization variables to solve for the variable combination that maximizes the overall system performance functional. The sum of the power allocation weights equals 1. The grid dispatch command requires the system to output a maximum power of 30kW to meet the emergency charging demand. Since the total demand power of 30kW is much greater than the sum of the maximum sustainable carrying power of all transmitting coil units (approximately 15kW), within the preset feasible region—that is, under the constraints that the compensation topology selection variables take all selectable values, the power allocation weights are between 0 and 1 and their sum equals 1, and the actual allocated power of each transmitting coil unit does not exceed its respective maximum sustainable carrying power—there is no feasible solution that satisfies all the constraints. If no feasible solution is found in step four that yields the optimal value for the system's overall performance functional, then step five is executed as a fallback.

[0127] Step 5: Based on the solution results from Step 4, control the reconfigurable compensation network of each transmitting coil unit to switch to the compensation topology corresponding to the optimal compensation topology selection variable. When no feasible solution exists, switch the compensation topology of each transmitting coil unit to the preset default topology, and perform proportional derating output limited to the maximum sustainable carrying power of each transmitting coil unit. In this embodiment, the preset default topology is the SS topology. The controller switches the compensation topology of each transmitting coil unit to the SS topology, and the actual output power of each transmitting coil unit is equal to its respective maximum sustainable carrying power, with the total output power being the sum of the maximum sustainable carrying powers (approximately 15kW). Simultaneously, adjust the pulse width modulation phase shift angle of the inverter of each transmitting coil unit according to the actual output power of each transmitting coil unit.

[0128] Step six: Repeat steps one through five at predetermined time intervals. In this embodiment, the predetermined time interval is 100 milliseconds. The controller continuously performs rolling optimization with a period of 100 milliseconds. When the temperature of any transmitting coil unit decreases and the maximum sustainable carrying power recovers, the feasible region becomes non-empty again, and the system automatically exits the fallback mode and returns to the normal optimal power regulation state.

[0129] Implementation results:

[0130] In this embodiment, under extreme high-temperature conditions, after the optimization decision unit detects no feasible solution, the system automatically switches to fallback mode within 100 milliseconds. The compensation topology of each transmitting coil unit switches to SS topology, with a total output power of approximately 15kW. Although this cannot meet the emergency charging demand of 30kW, the system maintains continuous power supply without interruption. The real-time temperature of all transmitting coil units does not exceed the hardware protection temperature threshold of 90°C, and the system operates safely. When the ambient temperature decreases or the temperature of some transmitting coil units drops, the feasible region becomes non-empty again, and the system automatically exits fallback mode, resuming normal optimal power regulation state, with the total output power gradually recovering to the required value.

[0131] Comparative Example 1

[0132] Purpose of implementation:

[0133] The purpose of this comparative example is to provide a traditional wireless charging system power adjustment method. By comparing it with Embodiment 1 of the present invention, the beneficial effects of the present invention in terms of overall system transmission efficiency, thermal balance, response speed and functional completeness are verified.

[0134] Implementation System:

[0135] The wireless charging system used in this comparative example includes a transmitter matrix, a receiver, and a controller.

[0136] The transmitter array consists of nine 3×3 transmitter coil units. Each transmitter coil unit includes a transmitter coil, a fixed compensation network (SS topology only, non-reconfigurable), a current sampling module, a voltage sampling module, and a temperature sensor. Each transmitter coil unit operates at a frequency of 85kHz and has a rated power of 3.3kW.

[0137] The receiver is a single receiving coil mounted on the bottom of the electric vehicle, containing both the receiving coil and a battery management system interface. The receiver communicates wirelessly with the controller via a Bluetooth communication module.

[0138] The controller is connected to each transmitting coil unit and receiver unit of the transmitter matrix. The controller includes a power distribution module and a temperature monitoring module.

[0139] Implementation steps:

[0140] Step 1: The receiving end sends the power requirement information to the transmitting end controller via the Bluetooth communication link.

[0141] Step two: Based on the received power demand, the transmitter controller uses a proportional distribution strategy to distribute the total power equally among the nine transmitter coil units, meaning that each transmitter coil unit has the same output power.

[0142] Step 3: Temperature sensors monitor the temperature of each transmitting coil unit in real time. When the temperature of any transmitting coil unit exceeds the preset safety threshold (85°C), the controller performs derating on that transmitting coil unit, reducing its output power until the temperature drops below the safety threshold.

[0143] Step four: The controller repeats the above steps every 500 milliseconds.

[0144] Implementation results:

[0145] Under the same test conditions (ambient temperature 25℃, total output power 20kW, receiver located at the center of the transmitter matrix), the performance indicators of this comparative example are as follows: the overall system transmission efficiency is 86.2%; the maximum temperature difference of the transmitter coil array is 18.5℃; the number of times the temperature exceeds the limit and triggers derating is 12 times within 1 hour; the power adjustment response time is 520 milliseconds; and V2G mode switching is not supported.

[0146] Compared to Examples 1-5 and Comparative Example 1, the comparative example presents a stark contrast. The comparative example represents a traditional cascaded wireless charging power regulation scheme, whose core shortcomings are: the compensation network is fixed in an SS topology, unable to reconfigure the topology according to changes in operating conditions; power allocation uses a proportional strategy, failing to consider efficiency and thermal state differences among transmitting coil units; thermal management is passively responsive, only derating after temperature exceeds limits, resulting in lag; receiver status awareness relies on independent communication links such as Bluetooth, increasing system complexity and potential failure points; it does not support V2G bidirectional energy interaction, preventing participation in grid peak shaving; and it lacks a fallback mechanism when no feasible solution exists, potentially leading to direct system shutdown. These shortcomings result in significant deficiencies in the comparative example's overall system transmission efficiency, thermal balance, response speed, and functional completeness.

[0147] In contrast, embodiments 1 to 5 of this invention systematically solve the aforementioned problems from five dimensions. Embodiment 1 demonstrates that in a single-receiver scenario, by dynamically switching the reconfigurable compensation network and jointly optimizing the power allocation weights, the overall system transmission efficiency is improved by more than 7 percentage points compared to the comparative embodiment. Embodiment 2 demonstrates that in a multi-receiver scenario, by separating and identifying multiple characteristic frequency points in the complex spectrum of reflection impedance, the power requirements of different devices are differentiated and independently allocated. Embodiment 3 demonstrates that in a V2G scenario, by dynamically adjusting the game relationship between efficiency weights and thermal risk weights through the energy feedback willingness coefficient, seamless switching between charging and feeding modes is achieved. Embodiment 4 demonstrates that in a dynamic charging scenario, by using look-forward prediction of the electromagnetic-thermal coupling transient model to drive automatic power migration, the temperature difference of the coil array is significantly reduced. Embodiment 5 demonstrates that under extreme high-temperature conditions, by using infeasible solution detection and a proportional derating fallback mechanism, the system can continuously supply power under any conditions.

[0148] The above are merely specific embodiments of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of protection of the claims.

[0149] In conclusion, the above are merely preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. An adaptive power regulation method for a wireless charging system, the method comprising: Includes the following steps: Step 1: Obtain the reflection impedance characteristic parameters of each transmitting coil unit; Step 2: Extract the coupling coefficient between each transmitting coil unit and the receiving end, the equivalent load resistance of the receiving end, and the characteristic parameters of the receiving end from the reflection impedance characteristic parameters; the characteristic parameters are mapped to the energy feedback willingness coefficient of the receiving end; Step 3: Collect the real-time temperature and ambient temperature of each transmitting coil unit; based on the real-time temperature and ambient temperature of each transmitting coil unit, as well as the coupling coefficient and equivalent load resistance obtained in Step 2, predict the temperature rise of each transmitting coil unit in the future time period, and calculate the maximum sustainable power carrying capacity of each transmitting coil unit in the time period based on the predicted temperature rise. Step 4: Using the compensation topology selection variables and power allocation weights of each transmitting coil unit as optimization variables, solve for the compensation topology selection variables and power allocation weights that make the overall system performance functional obtain the optimal value, and at the same time obtain the optimal compensation topology selection variables and optimal power allocation weights of each transmitting coil unit; the sum of the power allocation weights is equal to 1. The system overall performance functional is positively correlated with the system overall transmission efficiency and negatively correlated with the thermal risk penalty term of each transmitting coil unit. The weights of the system overall transmission efficiency and the thermal risk penalty term in the system overall performance functional are dynamically adjusted according to the magnitude of the energy feedback willingness coefficient. Step 5: Based on the solution results of Step 4, control the reconfigurable compensation network of each transmitting coil unit to switch to the compensation topology corresponding to the optimal compensation topology selection variable, and at the same time adjust the output power of each transmitting coil unit according to the optimal power allocation weight; Step Six: Repeat steps one through five at predetermined time intervals. 2.The adaptive power regulation method of a wireless charging system of claim 1, wherein, The method for obtaining the reflection impedance characteristic parameters in step one is as follows: inject a sweep frequency signal into each transmitting coil unit and obtain the complex spectrum of the reflection impedance between each transmitting coil unit and the receiving end; the frequency range of the sweep frequency signal is from the preset resonant frequency minus the preset sweep frequency bandwidth to the preset resonant frequency plus the preset sweep frequency bandwidth, and the preset sweep frequency bandwidth is 15% to 25% of the preset resonant frequency. 3.The adaptive power regulation method of a wireless charging system of claim 1, wherein, The method for extracting the coupling coefficient, equivalent load resistance, and characteristic parameters from the reflection impedance characteristic parameters in step two is as follows: the complex spectrum of the reflection impedance is fitted with the impedance frequency response of the preset equivalent circuit model, and the coupling coefficient, equivalent load resistance, and characteristic parameters are separated from the fitted parameters. The characteristic parameter is the offset of the resonant frequency in the complex spectrum of the reflection impedance relative to a preset reference frequency. 4.The adaptive power regulation method of a wireless charging system of claim 1, wherein, The reconfigurable compensation network includes at least two optional compensation topologies, including LCC topology, CLC topology and SS topology; the reconfigurable compensation network is composed of switching elements and multiple compensation capacitors and compensation inductors, and different compensation topologies are switched by controlling the on and off states of the switching elements. 5.The adaptive power regulation method of a wireless charging system of claim 1, wherein, The energy feedback willingness coefficient ranges from 0 to 1 and is calculated and generated by the battery management system of the receiving end based on the battery state of charge and grid dispatch instructions. The receiving end modulates its own bidirectional controllable rectifier inverter unit by switching, and superimposes the state information containing the energy feedback willingness coefficient onto the reflection impedance of the receiving end in the form of low-frequency spectral characteristics.

6. The adaptive power regulation method of a wireless charging system of claim 1, wherein, When the energy feedback willingness coefficient increases, the weight of the overall system transmission efficiency increases and the weight of the thermal risk penalty term decreases; when the energy feedback willingness coefficient decreases, the weight of the overall system transmission efficiency decreases and the weight of the thermal risk penalty term increases; in step five, the switching of the reconfigurable compensation network and the adjustment of the output power are executed synchronously at the start of the same pulse width modulation period.

7. The adaptive power regulation method of a wireless charging system of claim 1, wherein, In the solution process of step four, when the temperature rise of any of the predicted transmitting coil units exceeds the preset temperature safety threshold during the time period, the value of the thermal risk penalty term of the transmitting coil unit is increased, which reduces the optimal power allocation weight of the transmitting coil unit, while the optimal power allocation weight of other transmitting coil units is increased accordingly.

8. The adaptive power regulation method of a wireless charging system of claim 1, wherein, In step four, when there is no feasible solution that makes the overall system performance functional optimal, the compensation topology of each transmitting coil unit is switched to the preset default topology, and the output is proportionally dated to the maximum sustainable carrying power of each transmitting coil unit; the predetermined time interval mentioned in step six is ​​50 milliseconds to 100 milliseconds.

9. The adaptive power regulation method of a wireless charging system of claim 1, wherein, When the real-time temperature of any transmitting coil unit collected in step three exceeds the preset hardware protection temperature threshold, the reconfigurable compensation network of the transmitting coil unit is switched to bypass mode, the power allocation weight of the transmitting coil unit is set to 0, and the removed power allocation weight is allocated to other transmitting coil units; the bypass mode is the mode in which the transmitting coil unit is electrically disconnected from the transmitting end matrix.

10. An adaptive power regulation system for a wireless charging system, applied to the method of any one of claims 1-9, characterized in that, include: The transmitter matrix consists of N transmitter coil units, where N≥2. Each transmitter coil unit contains a reconfigurable compensation network, which contains at least two optional compensation topologies. The receiving end includes a bidirectional controllable rectifier-inverter unit; Impedance acquisition unit, used to acquire the reflection impedance characteristic parameters of each transmitting coil unit; The parameter extraction unit is used to extract the coupling coefficient between each transmitting coil unit and the receiving end, the equivalent load resistance of the receiving end, and the characteristic parameters of the receiving end from the reflection impedance characteristic parameters; the characteristic parameters are mapped to the energy feedback willingness coefficient of the receiving end. Temperature acquisition unit, used to acquire real-time temperature and ambient temperature of each transmitting coil unit; The thermal prediction unit is used to predict the temperature rise of each transmitting coil unit in the future time period based on the real-time temperature of each transmitting coil unit, the ambient temperature, the coupling coefficient, and the equivalent load resistance, and to calculate the maximum sustainable power carried by each transmitting coil unit in the time period. The optimization decision unit is used to solve for the compensation topology selection variables and power allocation weights that make the overall system performance functional obtain the optimal value, using the compensation topology selection variables and power allocation weights of each transmitting coil unit as optimization variables, and at the same time obtain the optimal compensation topology selection variables and optimal power allocation weights of each transmitting coil unit. An execution control unit is used to control the reconfigurable compensation network of each transmitting coil unit to switch to the corresponding compensation topology according to the optimal compensation topology selection variable, and to adjust the output power of each transmitting coil unit according to the optimal power allocation weight.

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