Electric vehicle wireless charging system and optimization method thereof

Abstract

The invention discloses an electric vehicle wireless charging system and an optimization method thereof. The electric vehicle wireless charging system comprises a transmitting end optimization module, a receiving end optimization module, a dynamic matching control module and an intelligent charging management module. The transmitting end optimization module is used for reducing magnetic field leakage in the energy transmission process through magnetic field focusing; the receiving end optimization module is used for detecting relative position deviation of the transmitting end and the receiving end and reducing external magnetic field interference; the dynamic matching control module is used for matching the impedance of the transmitting end and the receiving end in real time to reduce reflection loss; and the intelligent charging management module is used for implementing a segmented charging strategy according to the battery state and executing safety protection. By applying the technical scheme of the invention, the problems of high reflection loss caused by serious magnetic field leakage and impedance mismatch and low overall charging efficiency caused by lack of intelligent charging control in the existing wireless charging system of the electric vehicle can be solved.

Description

Technical Field

[0001] This application relates to the field of electric vehicle charging technology, specifically to a wireless charging system for electric vehicles and its optimization method. Background Technology

[0002] With the rapid development of the electric vehicle industry, wireless charging technology has gradually become an important development direction for electric vehicle charging due to its advantages such as no physical contact, convenient operation, and high safety. Currently, mainstream wireless charging technologies for electric vehicles are mainly based on the principle of electromagnetic induction. Their core structure includes a ground-based transmitting coil and an onboard receiving coil, achieving wireless energy transmission through an alternating magnetic field. In existing technologies, the transmitting and receiving coils constitute the basic energy transmission path. The system maintains energy transmission stability through a fixed-parameter impedance matching network and employs a single charging mode for battery charging management, while relying on a basic magnetic shielding structure to reduce external interference.

[0003] However, in existing technologies, the magnetic field transmission process is susceptible to energy diffusion due to positional offset, and impedance matching cannot adapt to dynamic changes in battery state. Furthermore, the charging strategy lacks fine-grained control over the entire battery lifecycle. Summary of the Invention

[0004] This application provides a wireless charging system for electric vehicles and its optimization method, which can solve the problems of serious magnetic field leakage, high reflection loss due to impedance mismatch, and low overall charging efficiency caused by lack of intelligent charging control in existing wireless charging systems for electric vehicles.

[0005] To achieve the above objectives, this application provides the following technical solution: This application provides a wireless charging system for electric vehicles, including a transmitter optimization module, a receiver optimization module, a dynamic matching control module, and an intelligent charging management module; The transmitter optimization module is used to reduce magnetic field leakage during energy transmission by focusing the magnetic field; The receiver optimization module is used to detect the relative positional offset between the transmitter and receiver and reduce external magnetic field interference; The dynamic matching control module is used to match the impedance of the transmitter and receiver in real time to reduce reflection loss; The intelligent charging management module is used to implement a segmented charging strategy and perform safety protection based on the battery status.

[0006] In one alternative embodiment, the transmitter optimization module includes a dual-coil coupling structure, which includes a main transmitting coil for generating a basic alternating magnetic field and an auxiliary focusing coil arranged around the main transmitting coil. The phase and amplitude of the current in the auxiliary focusing coil are adjustable to form a directional magnetic field beam.

[0007] In one alternative embodiment, the coil surface of the transmitter optimization module is covered with a magnetic core layer; The magnetic core layer is made of nanocrystalline alloy and has a honeycomb hollow structure with a hollow rate of 25%-35%.

[0008] In one optional embodiment, the dynamic matching control module includes: An LC adjustable resonant circuit includes an adjustable inductor and an adjustable capacitor. Impedance detection unit, used to acquire the equivalent impedance of the vehicle battery in real time; The control unit adopts an architecture combining MCU and FPGA. It is used to adjust the parameters of adjustable inductor and adjustable capacitor based on the data collected by the impedance detection unit and the position offset data of the receiving end, so as to achieve dynamic impedance matching.

[0009] In one optional embodiment, the receiver optimization module includes a position detection unit; The position detection unit uses a combination of infrared positioning and ultrasonic ranging to detect the lateral offset, longitudinal spacing, and angular offset between the receiving coil and the transmitting coil.

[0010] In one optional embodiment, the intelligent charging management module further includes an energy recovery unit; The energy recovery unit feeds back the remaining induced electrical energy from the receiving end to the power grid or energy storage unit through a bidirectional inverter circuit.

[0011] In one optional embodiment, the intelligent charging management module further includes protection mechanisms, including over-temperature protection, over-current / over-voltage protection, and abnormal magnetic field protection. When the temperature, current, voltage, or magnetic field leakage of the coil or battery exceeds a preset safety threshold, the protection mechanism is triggered to reduce the charging power or stop charging.

[0012] A second aspect of this application provides an optimization method for a wireless charging system for electric vehicles, applied to a wireless charging system, the method comprising: Magnetic field focusing adjustment steps: By adjusting the current phase and amplitude of the auxiliary focusing coil at the transmitting end, a directional magnetic field beam is formed to reduce magnetic field diffusion; Dynamic impedance matching steps: Real-time acquisition of battery equivalent impedance and position offset data, and adjustment of LC resonant network parameters at the transmitter and receiver to maintain impedance matching. Intelligent charging control steps: Based on the battery's real-time state of charge (SOC) and temperature, switch to the corresponding charging mode and perform safety protection and energy recovery during the charging process.

[0013] In one alternative embodiment, the method includes: When the battery's state of charge (SOC) is between 0% and 30%, a constant current fast charging mode is used. When the SOC is 30%-80%, a constant voltage current limiting mode is adopted; When the SOC is 80%-100%, trickle charging mode is used.

[0014] In one optional embodiment, the specific process of adjusting the LC resonant network parameters in the dynamic impedance matching step includes: The impedance value corresponding to the battery's SOC and temperature is collected in real time through the impedance detection unit. Based on the position offset data detected by the receiver, the optimal parameters of the adjustable inductor and adjustable capacitor are calculated using a preset matching algorithm. The control unit, based on an MCU and FPGA architecture, outputs control signals to adjust the adjustable inductor and adjustable capacitor in real time.

[0015] This application provides a wireless charging system for electric vehicles and its optimization method. The scheme reduces magnetic field leakage during energy transmission through a magnetic field focusing design in the transmitter optimization module, solving the energy loss problem caused by magnetic field diffusion and thus improving energy concentration. Based on the real-time detection of the relative positional offset between the transmitter and receiver by the receiver optimization module, this module simultaneously reduces external magnetic field interference, avoiding a decrease in coupling efficiency caused by positional offset. A dynamic matching control module performs real-time impedance matching between the transmitter and receiver, and this module eliminates reflection loss through dynamic parameter adjustment of the LC adjustable resonant circuit, ensuring maximum power transmission under different battery states and positional conditions. Furthermore, an intelligent charging management module implements a segmented charging strategy and executes safety protection based on battery state, balancing charging efficiency and battery life through mode switching, while a multi-dimensional protection mechanism ensures system operational safety. This design significantly improves energy transmission efficiency in all scenarios, increasing charging efficiency when there is no offset and maintaining stable output when positional offset exists, ultimately achieving high efficiency and reliability in the wireless charging process. Attached Figure Description

[0016] The accompanying drawings are for illustrative purposes only and are not intended to limit the scope of this application. Furthermore, the same reference numerals denote the same parts throughout the drawings. In the drawings: Figure 1 The overall architecture diagram of the wireless charging system for electric vehicles provided in this application is shown.

[0017] Figure 2 A schematic diagram of the transmitter dual-coil coupling structure and magnetic core layer design provided in this application is shown.

[0018] Figure 3 The circuit block diagram of the dynamic impedance matching control module provided in this application is shown.

[0019] Figure 4 A flowchart illustrating the optimization method for the wireless charging system for electric vehicles provided in this application is shown. Detailed Implementation

[0020] The technical solutions in the embodiments of the present invention will be clearly and completely described below. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0021] Example 1: Existing wireless charging systems for electric vehicles are mainly based on the principle of electromagnetic induction, consisting of a ground-based transmitting coil and an on-board receiving coil. In practical applications, three efficiency bottlenecks exist: magnetic field diffusion and leakage are common, especially when there is lateral offset or longitudinal spacing between the transmitting and receiving ends, significantly increasing energy loss; the equivalent impedance of the on-board battery dynamically changes with its state of charge (SOC) and temperature, while traditional systems use fixed-parameter impedance matching, leading to increased reflection losses; coil heating and high-frequency inverter switching losses further reduce overall efficiency.

[0022] Combination Figures 1 to 3 As shown, this application provides a wireless charging system for electric vehicles, including a transmitter optimization module, a receiver optimization module, a dynamic matching control module, and an intelligent charging management module. The transmitter optimization module is used to reduce magnetic field leakage during energy transmission by focusing the magnetic field. The receiver optimization module is used to detect the relative positional offset between the transmitter and receiver and reduce external magnetic field interference. The dynamic matching control module is used to match the impedance of the transmitter and receiver in real time to reduce reflection loss. The intelligent charging management module is used to implement a segmented charging strategy and perform safety protection according to the battery status.

[0023] The transmitter optimization module is the core execution unit for realizing the magnetic field focusing function. Its structure can adopt a dual-coil coupling design, including a main transmitting coil and an auxiliary focusing coil arranged around it. The main transmitting coil is used to generate a basic alternating magnetic field, and the current phase and amplitude of the auxiliary focusing coil can be independently adjusted to form a directional magnetic field beam in concert, suppressing the diffusion of the magnetic field to non-target areas. The coil body is a flat spiral structure, and the wire material can be oxygen-free copper or a high-conductivity copper alloy. Its surface is covered with a magnetic core layer 11. The material of the magnetic core layer 11 can be set according to the actual situation, such as one of nanocrystalline alloy, ferrite or amorphous alloy, and nanocrystalline alloy can be selected. The structure of the magnetic core layer 11 can be solid, honeycomb hollow or porous. The hollow ratio can be set according to the heat dissipation and magnetic concentration requirements, such as 25%–35%. This application embodiment does not make special limitations on this.

[0024] The receiver optimization module is a sensing and response unit that realizes position awareness and anti-interference functions. It includes a position detection unit and a built-in magnetic shielding layer. The position detection unit can use a combination of infrared positioning and ultrasonic ranging to obtain the lateral offset, longitudinal spacing and angular offset of the receiving coil relative to the transmitting coil in real time. The magnetic shielding layer is set on the periphery of the receiving coil or the back of the substrate. The material can be a high-permeability nickel-iron alloy, permalloy or laminated metal foil, which is used to attenuate the external magnetic field interference and prevent the transmitted magnetic field from affecting the electronic equipment in the vehicle. The data output by the position detection unit is transmitted to the dynamic matching control module in real time through the communication interface, which is one of the important bases for adjusting the impedance matching parameters.

[0025] The dynamic matching control module is the central control unit for achieving real-time impedance matching. It includes an LC adjustable resonant circuit, an impedance detection unit, and a control unit. The LC adjustable resonant circuit includes an adjustable inductor and an adjustable capacitor. Its adjustment range can be set according to the system operating frequency and power level. For example, the adjustable inductor range is 10–100μH, and the adjustable capacitor range is 10–100nF. This embodiment does not impose any special limitations on this. The impedance detection unit is used to collect the equivalent impedance data of the vehicle battery under different SOC and temperature conditions in real time. The control unit can adopt an architecture combining MCU and FPGA. The MCU is responsible for data processing, algorithm operation, and communication scheduling, while the FPGA is responsible for millisecond-level high-speed response and precise adjustment command output of LC parameters. This module dynamically updates the LC parameters according to a preset matching algorithm by fusing the data from the impedance detection unit and the receiver position offset data, so that the transmitter and receiver are always in a conjugate impedance matching state, thereby minimizing reflection loss.

[0026] The intelligent charging management module is the decision-making and execution unit for achieving intelligent and safe charging. It includes a segmented charging strategy execution module and a multi-dimensional safety protection mechanism. The segmented charging strategy switches modes based on the battery's real-time state of charge (SOC) and temperature parameters: when the SOC is in the 0%–30% range, constant current fast charging mode is activated; when the SOC is in the 30%–80% range, it switches to constant voltage current limiting mode; when the SOC is in the 80%–100% range, it enters trickle charging mode. The current / voltage thresholds corresponding to each mode can be adjusted according to the battery type (e.g., ...). The aging state settings (for ternary lithium, lithium iron phosphate) are not specifically limited in this application embodiment; the safety protection mechanism includes over-temperature protection, over-current / over-voltage protection and magnetic field abnormality protection: when the coil or battery temperature, charging circuit current / voltage, or magnetic field leakage intensity exceeds the preset safety threshold, the module triggers power reduction or stops charging, and issues an alarm signal through the human-machine interface or remote communication interface; the module can also integrate an energy recovery unit, which feeds back the unused induced electrical energy at the receiving end to the grid or local energy storage unit through a bidirectional inverter circuit, thereby improving the overall energy efficiency of the system.

[0027] Through the above technical solution, this application achieves the following: In the system initialization phase, the position detection unit completes relative position calibration, and the impedance detection unit obtains the initial equivalent impedance and sets the initial LC parameters; In the charging start-up phase, the transmitter optimization module adjusts the auxiliary focusing coil current to form a directional magnetic field beam, and the intelligent charging management module selects the corresponding charging mode according to the SOC; In the dynamic adjustment phase, each module continuously collects magnetic field distribution, position offset, battery impedance, and temperature data, and the dynamic matching control module adjusts the LC parameters and focusing coil excitation in a closed loop accordingly to maintain high energy concentration and low reflection loss; In the charging end or abnormal occurrence phase, the intelligent charging management module performs mode switching or protection actions. Therefore, the transmitter magnetic field focusing design reduces magnetic field leakage, the receiver position sensing and dynamic impedance matching work together to reduce mismatch reflection loss, and the segmented charging strategy and multiple protection mechanisms improve safety and battery life, thereby comprehensively improving wireless charging efficiency in all scenarios—the overall system efficiency can reach over 92% under no-offset conditions, and it can still stably maintain a transmission efficiency of over 85% under ±15cm lateral offset and ±10cm longitudinal spacing offset conditions.

[0028] Example 2: In one optional embodiment, this application also provides a wireless charging system for electric vehicles, wherein the transmitter optimization module includes a dual-coil coupling structure, the dual-coil coupling structure including a main transmitting coil for generating a basic alternating magnetic field, and an auxiliary focusing coil arranged around the main transmitting coil; The phase and amplitude of the current in the auxiliary focusing coil are adjustable to form a directional magnetic field beam.

[0029] The dual-coil coupling structure is a planar spiral layout, with the main transmitting coil and the auxiliary focusing coil coplanarly mounted on the same PCB substrate or winding frame, their axes coincident and centers aligned. The main transmitting coil is wound with Litz wire, with 12–20 turns and a wire diameter of 1.2–1.8 mm, and is used to generate a basic alternating magnetic field at an operating frequency of 85 kHz. The auxiliary focusing coil is arranged in a ring array, consisting of 4–8 independent windings. Each winding is evenly arranged along the outer periphery of the main transmitting coil, and its wire material, insulation class, and winding process are consistent with those of the main transmitting coil. The specific number of windings and their arrangement can be set according to actual conditions, and this application does not impose any special limitations on this.

[0030] The main transmitting coil is used to generate a basic alternating magnetic field, which is distributed in an approximately axisymmetric diffusion pattern and covers the effective area of ​​the receiving coil under no offset conditions. This basic magnetic field serves as the main channel for energy transmission, and its strength and frequency are determined by the inverter power supply. When in operation, a sinusoidal current with an effective value of 30–60A is passed through it.

[0031] The auxiliary focusing coils are arranged around the main transmitting coil, physically located in the outer ring area of ​​the main transmitting coil, maintaining a radial distance of 2–5 mm from the main transmitting coil. Each set of auxiliary focusing coils can be independently connected to the current adjustment circuit, and their current amplitude (adjustable from 0–25A) and phase (continuously adjustable from –90° to +90°) are controlled by digital potentiometers and high-speed H-bridge drive units, thereby synthesizing a compensating magnetic field with direction selectivity in space. After the compensating magnetic field is superimposed with the basic magnetic field generated by the main transmitting coil, the magnetic field vector distribution is reconstructed, so that the synthesized magnetic field is enhanced in the target receiving direction and attenuated in the lateral and vertical directions, ultimately forming a directional magnetic field beam with forward directionality.

[0032] Current phase adjustment refers to changing the phase difference between the current in the auxiliary focusing coil and the current in the main transmitting coil to regulate the interference mode between the compensation magnetic field and the main magnetic field: when the phase difference is 0°, the superposition effect is mainly amplitude enhancement; when the phase difference is ±45°, magnetic field gradient directional deflection can be achieved; when the phase difference is ±90°, it mainly affects the spatial rotation characteristics of the magnetic field and helps to suppress transverse eddy current loss; the phase adjustment accuracy can reach ±1°, which is achieved by the high-resolution digital phase generator embedded in the FPGA.

[0033] Current amplitude adjustment refers to dynamically adjusting the excitation current of each group of auxiliary focusing coils based on real-time collected magnetic field sensor array data to match the optimal focusing requirements under the current vehicle parking position; the amplitude adjustment range is 0–100% of the rated current, supporting independent adjustment of each group, as well as synchronous adjustment of groups; for example, all 4 groups can be excited with the same amplitude, or the 2 groups closer to the offset side can have their amplitude increased and the 2 groups on the opposite side can have their amplitude decreased, and the embodiments of this application do not make special limitations on this.

[0034] A directional magnetic field beam refers to a composite magnetic field distribution pattern in which, after the synergistic effect of the main and auxiliary coils, the magnetic field strength is not less than 85% of the peak value within a cone angle range of ±15° in the normal direction of the transmitting end, while it attenuates to less than 30% of the peak value in areas outside ±30°. The spatial pointing of this directional beam can be dynamically calibrated by adjusting the phase and amplitude combination of different sets of auxiliary focusing coils to adapt to the coupling center offset caused by lateral offset (±15cm), longitudinal spacing change (±10cm), or angular tilt (±5°) at the receiving end.

[0035] Through the above technical solution, this application achieves the following: based on the stable energy output provided by the main transmitting coil, a controllable compensating magnetic field is generated by using the auxiliary focusing coil arranged in a ring and its independently adjustable current phase and amplitude, which is superimposed with the main magnetic field to form a spatially directional directional magnetic field beam; this directional beam significantly constrains the magnetic field diffusion path, reduces the magnetic field leakage intensity in non-target areas, and improves the magnetic coupling coefficient between the transmitting end and the receiving end. In particular, it can maintain high-efficiency energy transmission even when the vehicle has parking deviation, thereby solving the technical problems of low energy utilization and strong electromagnetic interference caused by magnetic field divergence at the transmitting end.

[0036] Example 3: In one optional embodiment, this application also provides that the coil surface of the transmitter optimization module is covered with a magnetic core layer 11; the magnetic core layer 11 is made of nanocrystalline alloy material and has a honeycomb hollow structure with a hollow ratio of 25%–35%.

[0037] The magnetic core layer 11 covers the outer surface of the main transmitting coil and the auxiliary focusing coil of the transmitter optimization module. It is used to guide and constrain the alternating magnetic field path, enhance the concentration of the magnetic field in the receiving direction, and suppress lateral diffusion and vertical leakage magnetic field. The magnetic core layer 11 does not change the original geometric configuration and electrical connection relationship of the coil, but is integrated on the outside of the coil structure as an additional functional layer.

[0038] The magnetic core layer 11 is made of a nanocrystalline alloy, which is obtained by low-temperature annealing and crystallization of Fe–Si–B–Cu–Nb amorphous precursor. It has a typical saturation magnetic induction intensity Bs≥1.2T, initial permeability μi≥80000, and high-frequency loss (100kHz / 0.2T)≤0.3W / kg. Compared with traditional ferrite or silicon steel sheets, this material exhibits both high permeability and low eddy current loss characteristics within the 10–150kHz wireless charging operating frequency band, which is beneficial for improving magnetic field coupling efficiency and suppressing self-heating.

[0039] The core layer 11 has a honeycomb-like perforated structure, with the perforations arranged periodically in regular hexagons. Each perforated unit has a side length of 0.8–1.2 mm and a wall thickness of 0.15–0.25 mm. The overall perforation rate is controlled within the range of 25%–35%, and can be precisely adjusted by changing the unit size, wall thickness, and arrangement density. This structure significantly reduces the overall mass of the core and the cross-sectional area of ​​the eddy current path while maintaining the continuity of the effective magnetic circuit, thereby reducing eddy current losses. Simultaneously, it forms a through-type heat dissipation channel, promoting the convection and conduction of heat to the environment during coil operation.

[0040] The perforation rate is defined as the ratio of the total area of ​​the perforated region to the total projected area of ​​the magnetic core layer 11. A value range of 25%–35% is an experimentally verified equilibrium range: when the perforation rate is below 25%, heat dissipation improvement is limited and eddy current suppression effect weakens; when it is above 35%, magnetic circuit integrity decreases, leading to a reduction in magnetic field concentration ability and a decrease in coupling coefficient. In this embodiment, a perforation rate of 30% is selected, corresponding to a honeycomb unit side length of 1.0 mm and a wall thickness of 0.2 mm; however, those skilled in the art will understand that this perforation rate can be adaptively adjusted within the range of 25%–35% according to the actual coil power level, operating frequency, and heat dissipation requirements. This embodiment does not impose any special limitations on this.

[0041] A flexible insulating adhesive layer is provided between the magnetic core layer 11 and the coil surface. The material is high-temperature resistant organic silicone (temperature resistance ≥200℃) with a thickness of 0.05–0.15mm. This ensures the reliability of the structural fit and avoids interface peeling or stress cracking caused by the difference in thermal expansion coefficient.

[0042] Through the above technical solution, this application achieves a balance between magnetic field focusing performance and thermal management capability without increasing the size and weight of the transmitter: the nanocrystalline alloy material provides high magnetic permeability support, and the honeycomb hollow structure effectively alleviates the temperature rise and eddy current loss of the magnetic core while ensuring the magnetic flux guiding capability, so that the transmitter optimization module can maintain a stable magnetic field output under continuous high power conditions, thereby supporting the coordinated and efficient operation of the dynamic matching control module and the intelligent charging management module.

[0043] Example 4: In one optional embodiment, this application also provides a wireless charging system for electric vehicles. An LC adjustable resonant circuit includes an adjustable inductor and an adjustable capacitor. Impedance detection unit, used to acquire the equivalent impedance of the vehicle battery in real time; The control unit adopts an architecture combining MCU and FPGA. It is used to adjust the parameters of adjustable inductor and adjustable capacitor based on the data collected by the impedance detection unit and the position offset data of the receiving end, so as to achieve dynamic impedance matching.

[0044] The LC adjustable resonant circuit is located on the transmitting end and / or receiving end to form an adjustable resonant network to adapt to the system resonant frequency under different operating conditions. The inductance value of the adjustable inductor is in the range of 10μH–100μH, and can be implemented using a magnetic core adjustable inductor driven by a digital potentiometer or a microelectromechanical adjustable inductor based on MEMS technology. The capacitance value of the adjustable capacitor is in the range of 10nF–100nF, and can be implemented using a piezoelectric ceramic adjustable capacitor, a varactor diode array, or a relay-switched capacitor bank. The specific parameter combination of the adjustable inductor and adjustable capacitor can be configured according to the system operating frequency (e.g., 85kHz±5kHz), the relationship between coil self-inductance and mutual inductance, and the target resonant point. The adjustment method can be continuous or step-by-step, and this application embodiment does not impose any special limitations on this.

[0045] The impedance detection unit is integrated between the vehicle battery management system (BMS) and the wireless charging controller. By sampling the battery terminal voltage and current signals and combining them with a preset battery equivalent circuit model (such as the Thevenin model), it calculates the amplitude and phase of the battery equivalent impedance under the current SOC and temperature conditions in real time. The sampling period of the impedance detection unit is no more than 100ms and the sampling accuracy is no less than 0.5%. Its output data is transmitted to the control unit via an isolated communication interface (such as SPI isolation or CANFD). This unit can also receive the position offset data output by the receiver position detection unit as a cooperative input variable for impedance compensation to improve matching robustness.

[0046] The control unit adopts an architecture combining MCU and FPGA: the MCU runs the main control logic and executes impedance-position joint matching algorithms (such as lookup table method, fuzzy PID or lightweight neural network model) to complete parameter planning and safety verification; the FPGA receives the target parameter instructions issued by the MCU and directly drives the adjustment actuators of the adjustable inductor and adjustable capacitor at the hardware level, with a response latency of less than 1ms, ensuring the real-time and deterministic performance of LC parameter adjustment; the MCU and FPGA are interconnected through a high-speed parallel bus or Avalon-MM interface, with a data exchange bandwidth of not less than 50MB / s; this architecture supports a redundancy verification mechanism, and the FPGA can maintain the basic matching function according to the caching strategy when the MCU fails, ensuring the safe degraded operation of the system.

[0047] Dynamic impedance matching refers to the process during charging where the equivalent impedance of the vehicle battery fluctuates due to changes in SOC, temperature drift, or shifts in the relative position of the receiver (including lateral ±15cm, longitudinal ±10cm, and angular ±5°). The control unit continuously updates the parameter combination of the LC adjustable resonant circuit to keep the power transmission loop between the transmitter and receiver near the resonant state, and the reflection coefficient Γ is kept within the range of |Γ|≤0.15, thereby controlling the reflection loss to within 5%.

[0048] Through the above technical solution, this application achieves the following: During the wireless charging process of electric vehicles, when changes in battery state (SOC, temperature) and spatial position (lateral offset, longitudinal spacing, angular offset) cause dynamic fluctuations in the system's equivalent impedance, the adjustable inductor and capacitor parameters are adjusted in millisecond-level closed-loop manner through the cooperation of the LC adjustable resonant circuit, impedance detection unit, and MCU+FPGA collaborative architecture. This ensures that the transmitter and receiver are continuously in a high-efficiency resonant matching state, significantly reducing energy reflection caused by impedance mismatch and supporting the system to maintain a transmission efficiency of ≥85% under all operating conditions.

[0049] Example 5: In one optional embodiment, this application also provides a wireless charging system for electric vehicles, wherein the receiver optimization module includes a position detection unit; the position detection unit uses a combination of infrared positioning and ultrasonic ranging to detect the lateral offset, longitudinal spacing and angular offset between the receiving coil and the transmitting coil.

[0050] The position detection unit is located inside the receiver housing or on the edge, and maintains a fixed relative position with the receiving coil. Its installation position can be adapted to the vehicle layout. For example, it can be arranged in the four corners of the receiving coil, in a centrally symmetrical position, or evenly distributed along the circumference. This application does not impose any special limitations on this.

[0051] The infrared positioning section includes at least three sets of infrared transmitter-receiver pairs arranged non-collinearly. Each pair emits a modulated infrared beam toward a preset reference area at the transmitter and receives the reflected signal. By comparing the signal strength, time-of-flight difference, and phase difference of each pair, the lateral and angular offsets of the receiving coil relative to the transmitting coil are calculated. The infrared light source has a wavelength of 850nm or 940nm and is resistant to ambient light interference. Its emission power can be automatically adjusted according to the ambient illuminance to balance detection distance and power consumption control.

[0052] The ultrasonic ranging section includes at least two ultrasonic transceiver probes, which are respectively arranged on both sides of the reference axis of the receiver structure. The probes operate at a frequency of 40kHz, with a measurement range of 5cm–30cm and a resolution of ±0.5cm. The longitudinal distance between the receiving coil and the transmitting coil is calculated by using dual-channel time-of-flight (TOF) measurement combined with a geometric triangulation algorithm. The surface of the ultrasonic probe is covered with a hydrophobic and dustproof film to ensure long-term stable operation under complex conditions such as rain, snow, and dust.

[0053] "Lateral offset" refers to the displacement vector of the center projection point of the receiving coil relative to the center of the transmitting coil in the horizontal plane (XY plane). Its components can be directly calculated from infrared positioning data, with a typical tolerance range of ±15cm. "Longitudinal spacing" refers to the distance between the two coil planes in the normal direction (Z direction), which is mainly determined by ultrasonic ranging data, with a typical tolerance range of ±10cm. "Angular offset" includes the pitch angle around the X-axis, the roll angle around the Y-axis, and the yaw angle around the Z-axis, which are obtained by joint inversion of infrared multi-point signal differences, with a typical detection accuracy better than ±1.5°.

[0054] The data fusion of infrared positioning and ultrasonic ranging adopts a weighted Kalman filter algorithm: infrared data provides initial position values ​​with a high update rate (≥50Hz) but are susceptible to occlusion, while ultrasonic data provides longitudinal constraints with high accuracy (±0.5cm) and a low update rate (≤20Hz). The filter dynamically adjusts the weight coefficients according to the confidence of each sensor and outputs smooth, continuous, and non-jumping six-degree-of-freedom spatial pose parameters (X,Y,Z,θx,θy,θz). These parameters are transmitted in real time to the dynamic matching control module and the transmitter optimization module via CAN bus or SPI interface.

[0055] The housing of the position detection unit is made of flame-retardant PBT engineering plastic, with heat-conducting fins on the surface and mechanically coupled to the heat dissipation structure of the receiver. Its power supply is provided by the receiver rectification and voltage regulation circuit, with an operating voltage of 3.3V or 5VDC. The signal processing chip integrates ADC, timer and basic filtering logic, supports sleep wake-up mechanism, and is in low-power standby state when the vehicle has not entered the charging area, with power consumption of less than 100μW.

[0056] Through the above technical solution, this application achieves highly robust, high-precision, and all-dimensional perception of the spatial position deviation of the transmitter by the receiver: infrared positioning ensures rapid response and wide coverage, ultrasonic ranging compensates for the shortness of longitudinal distance accuracy, and the fusion of the two outputs stable and reliable lateral offset, longitudinal spacing, and angular offset data; this data serves as a key input for the dynamic matching control module to adjust LC parameters and for the transmitter optimization module to adjust the auxiliary focusing coil current, supporting the system to maintain efficient energy transmission in real-world scenarios such as inaccurate parking, road surface undulations, and changes in vehicle attitude.

[0057] Example 6: In one optional embodiment, the present application also provides that the intelligent charging management module further includes an energy recovery unit; the energy recovery unit feeds back the remaining induced electrical energy at the receiving end to the power grid or energy storage unit through a bidirectional inverter circuit.

[0058] The energy recovery unit is a component of the intelligent charging management module. Its input end is connected to the DC bus after rectification and filtering at the receiving end, and its output end is connected to the charging and discharging interface of the public power grid or local energy storage unit through an isolated DC / AC converter. This unit does not change the topology of the main charging circuit and only starts working during charging gaps, sudden load drops, or when the system enters standby mode.

[0059] The bidirectional inverter circuit is a full-bridge inverter topology with bidirectional energy flow capability, including four power switching devices (such as IGBT or SiCMOSFET), a drive circuit, a current / voltage sampling unit, and an isolated PWM control signal interface; its control logic is uniformly scheduled by the main control unit in the intelligent charging management module, and determines whether to enable energy feedback based on the DC bus voltage fluctuation trend at the receiving end, the change in current direction, and preset trigger conditions (such as the charging current being continuously lower than the threshold of 500mA for 200ms).

[0060] Residual induced energy refers to the induced energy that remains in the receiver's resonant network and rectifier-filter stage during wireless charging, even under conditions such as transmitter power adjustment, vehicle brief departure, battery near full charge and active output reduction, or external command to pause charging. This energy exists in the form of high-frequency AC or pulsating DC. After rectification, boosting, inversion, and synchronous grid connection in the energy recovery unit, it is converted into electrical energy that conforms to grid standards (such as GB / T19964-2012) or energy storage unit interface protocols (such as CAN2.0B communication + constant voltage current limiting charging and discharging mode).

[0061] Feedback to the grid refers to injecting recovered electrical energy into the low-voltage distribution network in the same frequency and phase manner through a grid-connected inverter, supporting unidirectional or bidirectional metering operation modes; the energy storage unit can be an on-board auxiliary power supply, a ground-side buffer lithium battery pack, or a supercapacitor module, and its capacity can be set from 0.5 to 5 kWh according to the system scale. The charging and discharging interface voltage level is matched with the DC bus of the receiving end, such as 48V, 350V, or 750V; the energy recovery unit performs SOC closed-loop management for the charging and discharging process of the energy storage unit. When the SOC of the energy storage unit is ≥90%, the feedback charging is automatically prohibited to avoid the risk of overcharging.

[0062] Key parameters in the bidirectional inverter circuit can be flexibly configured according to actual system requirements: the switching frequency can be 10kHz–100kHz; the output voltage accuracy is better than ±1%, and the total harmonic distortion (THD) is ≤3%; the energy recovery efficiency (from the DC bus input at the receiving end to the grid / energy storage unit output) is not less than 88%; this parameter range can be set according to actual conditions, for example, it can be a switching frequency of 20kHz, THD≤2.5%, and efficiency≥90%, or a switching frequency of 50kHz, THD≤3%, and efficiency≥88%. This application embodiment does not make any special limitation on this.

[0063] Through the above technical solution, this application realizes the effective capture and reuse of residual induced energy during the non-steady-state operation of the wireless charging system: due to the introduction of the energy recovery unit and the bidirectional inverter circuit, the receiving end is no longer a pure energy consumption node, but has dynamic energy routing capability; combined with the real-time perception and coordinated scheduling of the charging status by the intelligent charging management module, the remaining induced energy can be fed back to the grid or temporarily stored in the energy storage unit in a timely manner in typical scenarios such as charging pause, mode switching or abnormal exit, thereby reducing reactive power loss and heat loss, improving the overall energy utilization efficiency of the system, and is especially suitable for application scenarios with high frequency start-stop and intermittent load characteristics such as urban bus stations and centralized charging points for shared cars.

[0064] Example 7: To prevent safety accidents caused by overheating, overcurrent, overvoltage or abnormal magnetic field during charging, and to ensure the safety of personnel, vehicles and equipment.

[0065] In one optional embodiment, the present application also provides that the intelligent charging management module further includes a protection mechanism, which includes over-temperature protection, over-current / over-voltage protection and magnetic field abnormality protection; when the coil or battery temperature, current, voltage or magnetic field leakage exceeds a preset safety threshold, the protection mechanism is triggered to reduce the charging power or stop charging.

[0066] The protection mechanism is a closed-loop response unit integrated within the intelligent charging management module. Its input terminals are connected to a temperature sensor, a current / voltage sampling circuit, and a magnetic field detection sensor array, respectively, while its output terminal is connected to a dynamic matching control module and a transmitter drive circuit. The temperature sensor is located at the gap between the transmitting coil windings, the back of the receiving coil substrate, and key temperature measurement points of the battery module to collect real-time data on the temperature rise of the coil copper loss, the temperature rise of the iron core, and the surface temperature of the battery cells. The current / voltage sampling circuit uses a high-precision isolated Hall sensor and a resistor divider network, deployed on the inverter output side of the transmitter and the rectifier output side of the receiver, to synchronously monitor the instantaneous current and DC bus voltage in the charging circuit. The magnetic field detection sensor array consists of eight anisotropic magnetoresistive (AMR) sensors arranged in a ring, installed on the edge of the transmitter housing, to sense the three-dimensional spatial magnetic field distribution in real time and calculate the equivalent magnetic field leakage.

[0067] The preset safety thresholds for over-temperature protection include: transmitting coil temperature ≥ 105℃, receiving coil temperature ≥ 95℃, and battery cell surface temperature ≥ 60℃. When the temperature at any measuring point exceeds the corresponding threshold for 200ms, the protection mechanism initiates a tiered response: the first level reduces the charging power to 50% of the rated value; the second level stops charging and triggers an audible and visual alarm if the temperature does not drop after a 500ms delay. The preset safety thresholds for overcurrent / overvoltage protection include: charging current ≥ 1.2 times the rated current and DC bus voltage ≥ 1.15 times the rated voltage. When the sampled value exceeds the limit for 10 consecutive switching cycles... If a true overload is detected, the protection mechanism immediately cuts off the inverter bridge drive signal and blocks the restart command within the next 3 seconds. The preset safety threshold for magnetic field anomaly protection is: the magnetic field strength B measured at 1m from the edge of the transmitter is ≥100μT (frequency 100kHz–200kHz). This threshold is set according to GB / T37130—2018 "Limits for Human Exposure to Electromagnetic Fields in Vehicles". When the equivalent leakage magnetic field calculated by the magnetic field detection sensor array exceeds the threshold and lasts for 50ms, the protection mechanism simultaneously performs power reduction operation and pushes a "magnetic field shielding abnormality" prompt message to the vehicle human-machine interface.

[0068] Safety thresholds can be adaptively adjusted according to different vehicle configurations, environmental conditions, and battery chemistry systems. For example, for lithium iron phosphate battery systems, the battery temperature threshold for over-temperature protection can be set to 65°C. For high-altitude operating scenarios, the magnetic field leakage threshold can be lowered to 80 μT. This application does not impose any special limitations on the specific values ​​of each threshold, as long as they meet the requirements of automotive-grade functional safety ASIL-B level.

[0069] The operation of reducing charging power or stopping charging is uniformly scheduled by the protection logic submodule in the intelligent charging management module. This submodule is implemented with a dual redundancy architecture of hardware watchdog + software state machine. Its control signal is sent to the FPGA interrupt pin of the dynamic matching control module after opto-isolation to ensure that the response delay is ≤1ms. The charging stop action includes triple shutdown: shutting down the high-frequency inverter driver at the transmitting end, disconnecting the rectifier output relay at the receiving end, and setting the bidirectional inverter circuit to the energy recovery standby state.

[0070] Through the above technical solution, this application realizes an active protection mechanism that embeds multi-source sensor fusion into the intelligent charging management module. By setting up independent monitoring channels covering three types of physical quantities—thermal, electrical, and magnetic—and defining differentiated response strategies and graded action thresholds, the system can intervene as soon as signs of over-temperature, over-current / over-voltage, or magnetic field abnormalities appear, preventing the fault from escalating. At the same time, the protection action works in synergy with the dynamic matching control module and the energy recovery unit, ensuring both the reliability of safe shutdown and the operability of system recovery, thereby significantly improving the safety and robustness of the entire wireless charging process for electric vehicles.

[0071] Example 8: The technical problem to be solved by this invention is that existing wireless charging methods for electric vehicles lack a system-level coordinated control mechanism, making it difficult to achieve dynamic coupling and closed-loop optimization at the three levels of magnetic field focusing, impedance matching, and charging strategy. This results in low energy transmission efficiency, weak anti-offset capability, and insufficient battery health maintenance, especially under complex working conditions such as vehicle parking position deviation, dynamic changes in battery status, and environmental interference, the performance of which deteriorates significantly.

[0072] To address the aforementioned problems, this application provides an optimization method for a wireless charging system for electric vehicles, comprising the following steps: Magnetic field focusing adjustment steps: By adjusting the current phase and amplitude of the auxiliary focusing coil at the transmitting end, a directional magnetic field beam is formed to reduce magnetic field diffusion; Among them, the "auxiliary focusing coil" is the independent coil structure surrounding the main transmitting coil as defined in Example 2, and its adjustable current phase and amplitude are new technical features; "forming a directional magnetic field bundle" is the direct result of this technical feature in this step, which is used to constrain the spatial distribution of the magnetic field and suppress energy dissipation to the uncoupled region; "reducing magnetic field diffusion" is the technical effect achieved at the system level after the introduction of this technical feature, and its physical realization depends on the superposition relationship of the magnetic field vectors generated by the main transmitting coil and the auxiliary focusing coil.

[0073] In one alternative implementation, the adjustment method may be: based on the real-time magnetic field distribution data collected by the magnetic field detection sensor array, the phase difference compensation algorithm is executed by the MCU to calculate the current phase offset required by the auxiliary focusing coil relative to the main transmitting coil, and the amplitude is adjusted by a digital potentiometer and a programmable constant current source. In another alternative implementation, the adjustment method may include: pre-setting multiple sets of phase-amplitude combination parameter tables, each set of parameters corresponding to a typical offset condition (such as lateral ±5cm, ±10cm, ±15cm), and the control unit selecting and loading the corresponding parameters according to the offset type output by the receiver position detection unit; Furthermore, the adjustment method can also adopt a closed-loop feedback approach: with the stability of the amplitude of the induced voltage at the receiving end as the optimization target, the phase and amplitude of the auxiliary focusing coil are iteratively updated at a frequency of 10kHz through the FPGA until the induced voltage fluctuation rate is lower than ±1.5%.

[0074] Dynamic impedance matching steps: Real-time acquisition of battery equivalent impedance and position offset data, and adjustment of LC resonant network parameters at the transmitter and receiver to maintain impedance matching. Among them, "battery equivalent impedance" is a new technical feature, which refers to the complex impedance characteristics of the vehicle battery and its connecting lines in the wireless charging circuit under the current SOC, temperature and operating frequency, and its value changes dynamically with the charging process; "position offset data" is a new technical feature, which refers to the lateral offset, longitudinal spacing and angular offset obtained by infrared and ultrasonic fusion positioning in Example 5. This data reflects the degree of deterioration of the coil coupling state; "LC resonant network parameters" is a new technical feature, which specifically refers to the specific values ​​of the adjustable inductor and adjustable capacitor contained in the LC adjustable resonant circuit in Example 4. The two together determine the system resonant frequency and input impedance angle; the three constitute the joint input variables for dynamic matching, and none of them can be omitted.

[0075] In one alternative implementation, the adjustment method can be: using the real-time acquired battery equivalent impedance Z... batt Using the position offset data (Δx, Δy, θ) as input, and substituting it into a preset three-dimensional lookup table mapping model, the output is the corresponding optimal adjustable inductance L. opt With adjustable capacitor C opt The model was obtained through offline calibration, covering SOC 0%–100% and temperature. 20℃–60℃, offset ±15cm / ±10cm / ±5° full operating range; In another alternative implementation, the adjustment method may include: constructing an online least squares identification module, using the input voltage / current ratio at the transmitter as the observation variable, estimating the imaginary and real parts of the equivalent impedance in real time, and correcting the resonant point drift by combining the position offset data, thereby driving the FPGA to update the LC parameters; Furthermore, this adjustment method can also employ a hierarchical response mechanism: the MCU performs millisecond-level coarse adjustment (update cycle 50ms), and the FPGA performs microsecond-level fine adjustment (update cycle 200μs), with both working together to ensure impedance matching response bandwidth ≥5kHz.

[0076] Intelligent charging control steps: Based on the battery's real-time state of charge (SOC) and temperature, switch to the corresponding charging mode and perform safety protection and energy recovery during the charging process; Among them, "real-time state of charge (SOC) and temperature" is a new technical feature, which refers to the digital signal continuously output by the battery management system (BMS) through the sampling circuit. Its update frequency is not less than 1Hz, providing a basic input for segmented decision-making. "Switching the corresponding charging mode" is a new technical action, corresponding to the three modes of constant current fast charging, constant voltage current limiting, and trickle charging clearly defined in Example 9. The triggering condition of this action is determined by the combined SOC and temperature. "Executing safety protection and energy recovery" is a new set of technical functions, corresponding to the protection mechanism and energy recovery unit defined in Example 7 and Example 6, respectively. Whether it is activated depends on whether the real-time monitoring value exceeds the limit.

[0077] In one alternative implementation, the switching method may be: setting a two-dimensional SOC-temperature determination matrix, with each matrix unit bound to a charging mode and corresponding parameter threshold (e.g., maximum current of 30A in constant current stage and voltage of 3.65V / cell in constant voltage stage), and the control unit reading BMS data periodically and performing mode switching by looking up the table; In another alternative implementation, the switching method may include: introducing a fuzzy logic controller, taking the SOC change rate, temperature rise rate and current terminal voltage as input variables, and outputting a continuous power regulation coefficient to smoothly transition the boundaries of different charging stages and avoid current surges caused by mode abrupt changes; Furthermore, the execution method can also adopt an event-driven mechanism: when the over-temperature protection is triggered, the intelligent charging management module simultaneously reduces the charging power and activates the energy recovery unit, feeding the remaining induced electrical energy at the receiving end back to the energy storage unit through the bidirectional inverter circuit, thereby realizing the reuse of energy under fault conditions.

[0078] This application constrains the spatial path of energy transmission by coordinating the phase and amplitude of the auxiliary focusing coil in the magnetic field focusing adjustment step. Based on this, it ensures maximum power transfer at the circuit level by leveraging the joint response of LC parameters to battery impedance and positional offset in the dynamic impedance matching step. Furthermore, it achieves battery health maintenance and safe system operation at the control level through a segmented strategy driven by both SOC and temperature variables and a protection-recycling linkage mechanism in the intelligent charging control step. These three aspects are progressively advanced and interconnected, forming a closed-loop optimization across the entire chain from the physical field to the circuit domain to the control layer, effectively solving the technical challenges of low efficiency, poor robustness, and weak safety in wireless charging under complex operating conditions.

[0079] Example 9: In one optional embodiment, this application further provides a constant current fast charging mode when the battery state of charge (SOC) is 0%–30%; a constant voltage current limiting mode when the SOC is 30%–80%; and a trickle charging mode when the SOC is 80%–100%, including: Step 1: When the battery's state of charge (SOC) is 0%–30%, use constant current fast charging mode; Among them, "constant current fast charging mode" refers to controlling the charging current to remain constant at the preset maximum allowable current value during the charging process, while allowing the battery terminal voltage to rise naturally as the SOC increases; this mode is suitable for the initial energy replenishment stage after the battery is deeply discharged, and its technical function is to quickly increase the battery capacity with the maximum safe current and shorten the initial charging time. In one alternative implementation, the constant current control method can be: the battery current and voltage signals are collected in real time by the intelligent charging management module, and the MCU generates a PWM duty cycle adjustment command according to the preset current threshold (e.g., C / 2 to 1.5C, corresponding to different battery capacities and thermal management capabilities). The bidirectional inverter is controlled by the drive circuit to output a high-frequency AC power with a constant amplitude, so that the DC current after rectification at the receiving end is stabilized at the set value. In another alternative implementation, the constant current control method includes: dynamically correcting the current setpoint based on the real-time equivalent internal resistance change fed back by the impedance detection unit—when an increasing trend in internal resistance is detected, the target current is appropriately reduced to suppress temperature rise; Furthermore, this constant current control method adopts a closed-loop proportional-integral (PI) regulation mode: taking the deviation between the measured charging current and the target current as input, the PI controller outputs a modulation signal to drive the inverter bridge arm switching device to achieve millisecond-level current tracking response; Step 2: When the SOC is 30%–80%, adopt the constant voltage current limiting mode; The "constant voltage and current limiting mode" refers to stabilizing the charging voltage at the optimal charging voltage platform corresponding to the current battery temperature and SOC (e.g., 4.15–4.20V / cell for ternary lithium batteries and 3.60–3.65V / cell for lithium iron phosphate batteries), while limiting the charging current to a preset upper limit. The technical function of this mode is to balance charging efficiency and electrochemical aging rate, suppressing side reactions and extending cycle life while ensuring a relatively fast charging speed. In one alternative implementation, the constant voltage and current limiting control method can be: the intelligent charging management module uses a built-in lookup table (LUT) method, combined with real-time SOC and battery temperature to find the target charging voltage, and achieves coordinated control of voltage regulation and current limiting through a dual closed-loop structure of voltage outer loop + current inner loop; In another alternative implementation, the constant voltage current limiting control method includes: using the DC bus voltage after rectification and filtering at the receiving end as a feedback quantity, which is sampled by the ADC and sent to the MCU. The MCU performs digital PID calculation and outputs a duty cycle adjustment quantity to drive the inverter to adjust the power output at the transmitting end, so that the output voltage at the receiving end is stabilized at the target value. At the same time, the current feedback value is monitored, and once the current limiting threshold is exceeded, the current loop priority action is triggered. Furthermore, the constant voltage current limiting control method adopts a feedforward compensation strategy: based on the position offset data and the changing trend of LC parameters output by the dynamic matching control module, the transmission efficiency attenuation is estimated, and the target voltage setting value is finely adjusted in advance to offset the voltage drop caused by coupling deterioration. Step 3: When the SOC is 80%–100%, use trickle charging mode; Among them, "trickle charging mode" refers to continuously replenishing the battery with a very small current (e.g., below 0.05C) that is significantly lower than the rated capacity until the full charge cutoff condition is reached. The technical function of this mode is to complete the battery charge saturation process, avoid the risk of lithium plating, gas generation and thermal runaway caused by overcharging, and ensure the safety and capacity consistency of charging termination. In one alternative implementation, the trickle control method can be as follows: when the SOC ≥ 80% and the voltage rises to the full charge threshold and remains there for a certain period of time (e.g., 10 minutes), the intelligent charging management module gradually reduces the target current to a preset trickle value (e.g., 0.02C–0.05C) and controls the inverter output through pulsed low-frequency modulation (e.g., 1Hz square wave) to reduce the average power density and heat accumulation. In another alternative implementation, the trickle control method includes: adaptive adjustment based on the battery temperature change rate (dT / dt)—if the temperature rise rate is detected to exceed 0.5℃ / min, the trickle amplitude is further reduced or the intermittent period is extended; Furthermore, the trickle control method employs a voltage-time composite criterion termination mechanism: during the trickle stage, it synchronously monitors whether the terminal voltage enters a plateau period and whether the voltage change rate is lower than a threshold (e.g., <1mV / min), and determines that charging is complete after multiple conditions are met. This application divides the battery's State of Charge (SOC) into three ranges: 0%–30%, 30%–80%, and 80%–100%. Within each range, it configures constant-current fast charging, constant-voltage current-limiting, and trickle charging modes, respectively, achieving refined adaptation to the entire battery lifecycle charging process. Leveraging this SOC zoning characteristic, the system can automatically switch to the most suitable voltage / current control strategy based on the electrochemical response characteristics of different ranges. This not only increases the effective charging amount per unit time but also significantly reduces the probability of lithium plating in high SOC regions and the risk of polarization overvoltage in low SOC regions. Furthermore, each charging mode relies on data collaboration between the intelligent charging management module and the dynamic matching control module to ensure that the power output is always under the dual constraints of magnetic field focusing optimization and impedance matching optimization, thereby improving charging efficiency while also considering safety and battery health.

[0080] Example 10: In an optional embodiment, this application also provides a specific process for adjusting the parameters of the LC resonant network during the dynamic impedance matching step, including: Step 1: Real-time acquisition of the impedance values ​​corresponding to the battery's SOC and temperature using the impedance detection unit; The impedance detection unit is an embedded detection circuit located on the vehicle-mounted receiver side. Its input is connected to the battery management system (BMS) communication interface to periodically read the SOC value and battery cell / module temperature data output by the BMS. The impedance value corresponding to SOC and temperature refers to the equivalent series impedance (ESR) and capacitive reactance components mapped by a pre-stored battery electrochemical impedance spectroscopy (EIS) lookup table model. This model was established through calibration experiments and covers the impedance change law of ternary lithium and lithium iron phosphate batteries under the conditions of -20℃ to 60℃ and SOC 0% to 100%. This impedance value serves as the reference input parameter for dynamic matching and does not depend on the application of an additional excitation signal, thus avoiding the introduction of measurement interference. In one alternative implementation, the impedance acquisition method is as follows: based on the SOC and temperature combination reported by the BMS, the corresponding initial impedance value is directly retrieved from the locally stored two-dimensional lookup table, and a dynamic correction term caused by real-time current ripple is superimposed. In another alternative implementation, the impedance acquisition method includes: inputting the four-dimensional data of voltage, current, SOC and temperature provided by the BMS into a lightweight neural network model, and outputting the equivalent impedance amplitude and phase; Furthermore, the impedance acquisition method employs the following steps: inserting a millisecond-level constant current disturbance during the charging gap, calculating the transient impedance in conjunction with the voltage response slope, and then weighted and fused with the lookup table results; Step 2: Combining the position offset data detected by the receiver, calculate the optimal parameters of the adjustable inductor and adjustable capacitor using a preset matching algorithm; The position offset data comes from the position detection unit that integrates infrared positioning and ultrasonic ranging, including the lateral offset Δx, longitudinal spacing Δz, and axial angle θ, with an accuracy better than ±0.5mm and ±0.3°. The preset matching algorithm is a nonlinear multi-objective optimization algorithm with the goal of minimizing the reflection coefficient Γ. The constraints include maintaining the LC resonant frequency at 85kHz±2kHz, adjusting the adjustable inductor range from 10–100μH, and adjusting the adjustable capacitor range from 10–100nF. The algorithm uses the position offset data and the obtained impedance value as input variables and outputs a combination of LC parameters that satisfies the system resonance condition and maximizes energy transmission efficiency. In one alternative implementation, the matching algorithm is as follows: an empirical fitting function k=f(Δx,Δz,θ) is constructed between the transmit-receive coupling coefficient k and the position offset, and then substituted into the impedance matching equation Z. in =Z0·(1 k²) - ¹, the LC value required for inverse solution; In another alternative implementation, the matching algorithm includes: an offline-trained support vector regression (SVR) model with Δx, Δz, θ, SOC, and temperature as feature inputs and optimal L and C as output labels, which is then deployed on an MCU for online inference; Furthermore, the matching algorithm employs an online iterative search method based on gradient descent, performing parameter probing, reflection power sampling, and direction update closed loop in the FPGA at a clock cycle of 100kHz, converging to a local optimum. Step 3: The control unit of the MCU and FPGA architecture outputs control signals to adjust the adjustable inductor and adjustable capacitor in real time; In this system, the control units of the MCU and FPGA architecture follow the definition in Example 4. The MCU is responsible for running the matching algorithm, managing communication and fault diagnosis, while the FPGA is responsible for executing high-speed low-level control. The control signals are digital PWM signals or I²C instructions, which drive the digital potentiometer-type magnetic core bias circuit with adjustable inductors and the solid-state relay array or varactor diode bias circuit with adjustable capacitors, respectively. The adjustment action response delay is ≤200μs, and the parameter update cycle is configurable from 10ms to 100ms. In one alternative implementation, the adjustment method is as follows: the FPGA generates a PWM waveform with the corresponding duty cycle by looking up a table based on the target L / C value sent by the MCU, and controls the DC bias current of the magnetic core after low-pass filtering, thereby continuously adjusting the inductance value; In another alternative implementation, the adjustment method includes: the FPGA writes register values ​​to the integrated programmable capacitor chip via the I²C bus, switching the parallel / series combination of the internal MOS capacitor array to achieve step-by-step capacitor adjustment; Furthermore, the adjustment method employs the following approach: the MCU and FPGA work together to complete closed-loop verification. After the FPGA performs the adjustment, it triggers the impedance detection unit to sample again. If the measured reflection coefficient Γ is not lower than the threshold of 0.15, the secondary fine-tuning process is initiated. This application jointly models the equivalent impedance corresponding to the battery state (SOC and temperature) with the three-dimensional position offset data of the receiver, generates the optimal LC parameters with the help of a preset matching algorithm, and achieves millisecond-level closed-loop adjustment based on the MCU+FPGA heterogeneous architecture. This enables the transmitter and receiver to maintain high-precision impedance matching under multiple dynamic disturbances such as vehicle parking deviation, battery aging, and temperature rise. It not only significantly reduces high-frequency reflection loss and improves the stability of energy transmission efficiency, but also avoids the frequency offset detuning and heat aggravation problems caused by traditional fixed parameter matching, providing deterministic technical support for reliable wireless charging in all scenarios.

[0081] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. 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. A wireless charging system for electric vehicles, characterized in that, It includes a transmitter optimization module, a receiver optimization module, a dynamic matching control module, and an intelligent charging management module; The transmitter optimization module is used to reduce magnetic field leakage during energy transmission by focusing the magnetic field; The receiver optimization module is used to detect the relative positional offset between the transmitter and receiver and reduce external magnetic field interference. The dynamic matching control module is used to match the impedance of the transmitter and receiver in real time to reduce reflection loss. The intelligent charging management module is used to implement a segmented charging strategy and perform safety protection based on the battery status.

2. The wireless charging system for electric vehicles according to claim 1, characterized in that, The transmitter optimization module includes a dual-coil coupling structure, which includes a main transmitting coil for generating a basic alternating magnetic field and an auxiliary focusing coil arranged around the main transmitting coil. The phase and amplitude of the current in the auxiliary focusing coil are adjustable to form a directional magnetic field beam.

3. The wireless charging system for electric vehicles according to claim 1, characterized in that, The coil surface of the transmitter optimization module is covered with a magnetic core layer; The magnetic core layer is made of nanocrystalline alloy and has a honeycomb hollow structure with a hollow rate of 25%-35%.

4. The wireless charging system for electric vehicles according to claim 1, characterized in that, The dynamic matching control module includes: An LC adjustable resonant circuit, wherein the LC adjustable resonant circuit includes an adjustable inductor and an adjustable capacitor; Impedance detection unit, used to acquire the equivalent impedance of the vehicle battery in real time; The control unit adopts an architecture combining MCU and FPGA, and is used to adjust the parameters of the adjustable inductor and adjustable capacitor according to the data collected by the impedance detection unit and the position offset data of the receiving end, so as to achieve dynamic impedance matching.

5. The wireless charging system for electric vehicles according to claim 1, characterized in that, The receiver optimization module includes a position detection unit; The position detection unit uses a combination of infrared positioning and ultrasonic ranging to detect the lateral offset, longitudinal spacing, and angular offset between the receiving coil and the transmitting coil.

6. The wireless charging system for electric vehicles according to claim 1, characterized in that, The intelligent charging management module also includes an energy recovery unit; The energy recovery unit feeds back the remaining induced electrical energy from the receiving end to the power grid or energy storage unit through a bidirectional inverter circuit.

7. The wireless charging system for electric vehicles according to claim 1, characterized in that, The intelligent charging management module also includes a protection mechanism, which includes over-temperature protection, over-current / over-voltage protection, and abnormal magnetic field protection. When the temperature, current, voltage, or magnetic field leakage of the coil or battery exceeds a preset safety threshold, the protection mechanism is triggered to reduce the charging power or stop charging.

8. An optimization method for a wireless charging system for electric vehicles, characterized in that, Applied to the wireless charging system as described in any one of claims 1-7, the method comprises: Magnetic field focusing adjustment steps: By adjusting the current phase and amplitude of the auxiliary focusing coil at the transmitting end, a directional magnetic field beam is formed to reduce magnetic field diffusion; Dynamic impedance matching steps: Real-time acquisition of battery equivalent impedance and position offset data, and adjustment of LC resonant network parameters at the transmitter and receiver to maintain impedance matching. Intelligent charging control steps: Based on the battery's real-time state of charge (SOC) and temperature, switch to the corresponding charging mode and perform safety protection and energy recovery during the charging process.

9. The optimization method for the wireless charging system for electric vehicles according to claim 8, characterized in that, The method includes: When the battery's state of charge (SOC) is between 0% and 30%, a constant current fast charging mode is used. When the SOC is 30%-80%, a constant voltage current limiting mode is adopted; When the SOC is 80%-100%, trickle charging mode is used.

10. The optimization method for the wireless charging system for electric vehicles according to claim 8, characterized in that, The specific process of adjusting the LC resonant network parameters in the dynamic impedance matching step includes: The impedance value corresponding to the battery's SOC and temperature is collected in real time through the impedance detection unit. Based on the position offset data detected by the receiver, the optimal parameters of the adjustable inductor and adjustable capacitor are calculated using a preset matching algorithm. The control unit, based on an MCU and FPGA architecture, outputs control signals to adjust the adjustable inductor and adjustable capacitor in real time.

Images