Wireless charging foreign object detection method and system

Abstract

The application discloses a wireless charging foreign matter detection method and system, and belongs to the technical field of wireless charging. The method comprises the following steps: establishing a coded nonlinear frequency point set; exciting a target microzone on a wireless charging device according to the coded nonlinear frequency point set; obtaining the complex impedance of the target microzone and calculating the phase in each frequency point stable region after excitation, and collecting the phase sequence; calculating the rotation stability index and the modal disturbance index according to the phase sequence; and detecting foreign matters according to the rotation stability index and the modal disturbance index. The application breaks the system steady-state response condition through non-monotonic frequency hopping excitation, utilizes the phase rotation inertia difference of different materials in the frequency jump process, extracts the phase rotation dynamics characteristics, and realizes the distinction between legal devices and metal foreign matters in the physical nature.

Description

Technical Field

[0001] This invention belongs to the field of wireless charging technology. Specifically, this invention relates to a method and system for detecting foreign objects in wireless charging. Background Technology

[0002] Existing vehicle-mounted wireless charging systems typically transmit energy based on the principle of electromagnetic induction, with the transmitting coil and receiving coil forming a resonant coupling system.

[0003] However, existing technologies rely on single-frequency impedance detection or resonance curve analysis under monotonic frequency sweep, identifying foreign objects solely through amplitude changes or frequency shifts. This method has low sensitivity to thin metal sheets (such as aluminum foil), small metal particles, and attached foreign objects, making it prone to missed detections and posing safety hazards.

[0004] Furthermore, existing detection methods all perform measurements after the system reaches a steady state, neglecting a crucial physical fact: the dynamic response processes of legitimate devices (including resonant circuits) and metallic foreign objects to frequency abrupt changes are fundamentally different. Current technologies fail to utilize this difference, thus losing key information for distinguishing between the two. Summary of the Invention

[0005] This invention aims to overcome the shortcomings of existing technologies and proposes a wireless charging foreign object detection method and system to achieve the following objectives: by disrupting the steady-state response conditions of the system through non-monotonic frequency hopping excitation, and by utilizing the difference in phase rotation inertia of different materials during the frequency hopping process, the phase rotation dynamic characteristics are extracted, thereby realizing the physical distinction between legitimate devices and metallic foreign objects.

[0006] To achieve the above objectives, the technical solution adopted by the present invention is as follows:

[0007] This invention provides a method for detecting foreign objects in wireless charging devices, which includes:

[0008] Establish a set of coded nonlinear frequency points;

[0009] The target micro-region on the wireless charging device is excited according to the coded nonlinear frequency point set;

[0010] In the stable region of each frequency point after excitation, the complex impedance of the target micro-region is obtained and the phase is calculated. The phase sequence is then obtained by summarizing the results.

[0011] Calculate the rotational stability index and modal perturbation index based on the phase sequence;

[0012] Foreign object detection is performed based on the rotational stability index and modal perturbation index.

[0013] Furthermore, in the coded nonlinear frequency point set, the output frequency of each frequency point is within a preset frequency range; the difference between the output frequencies of two adjacent frequency points is a random value; and each frequency point is arranged in a random order in the set.

[0014] Furthermore, the excitation duration of each frequency point is within a preset time range; the excitation amplitude of each frequency point is within a preset safe amplitude range.

[0015] Furthermore, the frequency stability region refers to the period of time during which the excitation continues for a preset period of time for any frequency point, after which the remaining excitation time is considered as the frequency stability region.

[0016] Furthermore, the step of obtaining the complex impedance of the target micro-region and calculating the phase includes:

[0017] For frequency point f i The voltage V of the target micro-region is collected within its frequency stability region. i Current I i ; i represents the number of frequency points;

[0018] Calculate the complex impedance Z(f) i ):

[0019] Z(f i ) =V i / I i ;

[0020] According to the complex impedance Z(f) i Calculate the phase φ(f) i ):

[0021] φ(f i =arctan(Im(Z(f) i )) / Re(Z(f i )));

[0022] Among them, Im(Z(f) i )) represents the complex impedance Z(f i The imaginary part of Re(Z(f)); i )) represents the complex impedance Z(f i The real part of ).

[0023] Furthermore, the rotational stability index is calculated based on the phase sequence, including: Calculate the first-order phase rotational velocity Q(i): Q(i)=(φ(f i+1 )-φ(f i )) / (f i+1 -f i ); Wherein, φ(f i) represents the i-th frequency point f i The measured phase; φ(f i+1 ) represents the (i+1)th frequency point f i+1 The measured phase; i represents the number of frequency points; Calculate the rotational stability index Sθ: Sθ=Σ|Q(i+1)-Q(i)|; Where Q(i+1) represents the (i+1)th frequency point f i+1 The first-order phase rotation velocity; Q(i) represents the i-th frequency point f i The first-order phase rotation speed.

[0024] Furthermore, the modal perturbation index is calculated based on the phase sequence, including:

[0025] M=[ Σ (φ(f i )-φ ref (f i ))² ] 1 / 2 ;

[0026] Where M represents the modal perturbation index; φ(f i ) represents the i-th frequency point f i The measured phase; φ ref (f i ) represents the i-th frequency point f i The reference phase value.

[0027] Furthermore, foreign object detection is performed based on the rotational stability index and modal perturbation index, including:

[0028] Construct a security decision function P safe :

[0029] P safe =w1·Sθ norm +w2·M norm ;

[0030] Wherein, Sθ norm M represents the normalized rotational stability index; norm w1 represents the normalized modal perturbation index; w2 represents the preset weight coefficients, which sum to 1.

[0031] Furthermore, foreign object detection is performed based on the rotational stability index and modal perturbation index, including:

[0032] If the P safe The function value is greater than or equal to the preset threshold P. th If the condition is met, it is determined that there is a foreign object in the current target micro-region; otherwise, there is no foreign object.

[0033] The present invention also provides a wireless charging foreign object detection system, using the above-described wireless charging foreign object detection method, the system comprising:

[0034] Multi-coil transmitting array, encoding excitation control module, impedance acquisition module, phase calculation and dynamic analysis module, and decision controller;

[0035] The coding excitation control module is used to establish a set of coded nonlinear frequency points and to excite the target micro-region on the multi-coil transmitting array according to the set of coded nonlinear frequency points.

[0036] The impedance acquisition module is used to acquire the complex impedance of the target micro-region and calculate the phase in the stable region at each frequency point after excitation, and summarize them to obtain the phase sequence;

[0037] The phase calculation and dynamic analysis module is used to calculate the rotational stability index and modal perturbation index based on the phase sequence.

[0038] The determination controller is used to detect foreign objects based on the rotational stability index and the modal disturbance index.

[0039] The technical effects of this invention are as follows:

[0040] This invention disrupts steady-state conditions through non-monotonic frequency-hopping excitation and utilizes the difference in phase rotation inertia of different materials as a detection basis. This innovative principle allows detection to move beyond static threshold comparisons and delve into the dynamic nature of the material's electromagnetic response, fundamentally improving foreign object detection capabilities. Furthermore, this invention enhances foreign object detection sensitivity by employing rotational stability indices and modal perturbation exponents. Attached Figure Description

[0041] Figure 1 A flowchart of a wireless charging foreign object detection method provided in an embodiment of the present invention;

[0042] Figure 2 This is a structural block diagram of a wireless charging foreign object detection system provided in an embodiment of the present invention. Detailed Implementation

[0043] The specific embodiments of the present invention will be further described in detail below with reference to the accompanying drawings. This is to help those skilled in the art to have a more complete, accurate, and in-depth understanding of the inventive concept and technical solutions of the present invention, and to facilitate its implementation. It should be noted that the terms "first," "second," etc., used in this application are only for the convenience of describing the technical solutions and to distinguish components; the corresponding component configurations may be the same or different, and are not intended to limit the scope of this application. To make the technical solutions of the present invention clearer, the present invention will be explained and illustrated through the following embodiments.

[0044] Wireless charging technology is now widely used in consumer electronics, smart vehicles, smart homes, and portable industrial devices. Electromagnetic induction wireless charging, with its core advantages of simple structure, high transmission efficiency, and controllable cost, has become the mainstream application solution in the market. During the operation of a wireless charging system, the transmitting coil array generates an alternating magnetic field, using electromagnetic coupling to transmit wireless power to the receiving device. However, if there are conductive metal objects such as coins, keys, metal scraps, can fragments, or metal patches between the charging transmitter panel and the device being charged, these objects will generate eddy currents under the influence of the alternating magnetic field. This can lead to a series of problems, including eddy current heating, magnetic field distortion, and electromagnetic coupling parameter deviation. These problems can range from a significant decrease in wireless charging transmission efficiency, abnormally high charging power consumption, and severe device overheating to, in severe cases, high-temperature burning of the metal object, melting of the charging panel, short circuit failure, and even major safety hazards such as fire and explosion. Therefore, high-precision and high-reliability foreign object detection technology is the core guarantee for the safe, stable, and compliant operation of wireless charging devices.

[0045] However, existing wireless charging foreign object detection technologies have technical defects such as low feature discrimination due to steady-state excitation, single detection dimension, and high false positive and false negative rates. They cannot distinguish the electromagnetic response characteristics of legitimate charging devices from those of metallic foreign objects from a physical perspective, making it difficult to meet the high-precision, high-reliability, all-time, and all-scenario foreign object safety detection requirements of high-end wireless charging devices.

[0046] Therefore, this embodiment provides a method for detecting foreign objects in wireless charging. By disrupting the steady-state response conditions of the system through non-monotonic frequency hopping excitation, and utilizing the difference in phase rotation inertia of different materials during the frequency hopping process, the method extracts the phase rotation dynamic characteristics, thereby distinguishing legitimate devices from metallic foreign objects from a physical perspective.

[0047] The technical principle is as follows: When an alternating magnetic field acts on a conductive material, eddy currents are induced within the material. The distribution and intensity of these eddy currents depend on the material's conductivity, permeability, geometry, and the frequency of the applied magnetic field. For legitimate receiving devices, they typically contain a carefully designed receiving coil, rectifier circuit, resonant compensation network, and load management circuit. These components constitute an electromagnetic system with a specific resonant frequency and quality factor. When the applied excitation frequency changes, the response of a legitimate device depends not only on the current excitation frequency but also on the inertia of its internal energy storage elements (inductors, capacitors), exhibiting a phase rotation inertia. That is, the phase does not change instantaneously with a sudden change in frequency but gradually adjusts according to the system's own dynamic characteristics.

[0048] In contrast, while metallic foreign objects (such as coins, keys, and aluminum foil) also generate eddy currents in alternating magnetic fields, their electromagnetic response characteristics differ fundamentally from those of legitimate devices. Metallic foreign objects typically lack a resonant structure; their impedance characteristics are primarily determined by eddy current losses and hysteresis losses, and these losses respond more directly and rapidly to frequency changes. When the excitation frequency changes abruptly, the phase response of the metallic foreign object almost instantaneously follows the frequency change, and its phase rotational inertia is significantly smaller than that of legitimate devices.

[0049] Based on the above technical principles, this embodiment provides a method for detecting foreign objects in wireless charging devices, such as... Figure 1 As shown, the specific method includes the following steps:

[0050] Establish a set of coded nonlinear frequency points;

[0051] The target micro-region on the wireless charging device is excited according to the coded nonlinear frequency point set;

[0052] In the stable region of each frequency point after excitation, the complex impedance of the target micro-region is obtained and the phase is calculated. The phase sequence is then obtained by summarizing the results.

[0053] Calculate the rotational stability index and modal perturbation index based on the phase sequence;

[0054] Foreign object detection is performed based on the rotational stability index and modal perturbation index.

[0055] Before proceeding with the overall detection process in this embodiment, a robust detection triggering mechanism is established. The triggering methods for foreign object detection in wireless charging in this embodiment include: detecting an object placed on the wireless charging device, or the wireless charging device periodically and automatically triggering the foreign object detection. The object placement triggering mode is an immediate trigger detection. When the pressure sensor, capacitive sensor, or electromagnetic identification module of the wireless charging device detects an object placed in the micro-area identification area of ​​the charging panel, the foreign object detection process is immediately initiated. This is a pre-charging safety detection, which can prevent the safety risks of high-power charging with foreign objects at the source. The periodic automatic triggering mode is a periodic inspection detection. The wireless charging device automatically initiates the foreign object detection process according to a preset time cycle in standby or charging conditions, polling and detecting each charging micro-area. This is specifically used to monitor for accidentally dropped or displaced metal foreign objects during charging, filling the technical gap of traditional technology's lack of monitoring throughout the charging process. After the wireless charging foreign object detection is triggered, the wireless charging device first prohibits high-power output and then enters a low-power detection mode to begin executing the specific process of wireless charging foreign object detection.

[0056] To perform foreign object detection in wireless charging, it is first necessary to establish a set of coded nonlinear frequency points. A set of coded nonlinear frequency points is a collection of multiple frequency points, which can be exemplified by the following formula:

[0057] F = {f1, f3, f2, f5, f4, f7, f6 … fi};

[0058] Where F represents the set of coded nonlinear frequency points; i represents the number of frequency points.

[0059] The coded nonlinear frequency point set constructed in this embodiment needs to meet three core conditions: the output frequency of each frequency point is within a preset frequency range; the difference between the output frequencies of two adjacent frequency points is a random value, i.e., the frequency intervals are not equal; and the frequency points are arranged in a random order in the set, i.e., the arrangement order is non-monotonic. These three conditions work together to ensure that the excitation signal has sufficient complexity and unpredictability, thereby effectively disrupting the steady-state response conditions of the system.

[0060] Regarding the selection of the frequency range, this embodiment sets the frequency point set coverage range between 85kHz and 135kHz. This frequency range selection is based on several technical considerations: First, this frequency band is located in the low-frequency operating range commonly used in wireless charging systems, is compatible with the operating frequencies of mainstream wireless charging standards, and is easy to implement on existing hardware platforms; second, the frequency range of 85kHz to 135kHz is wide enough to accommodate multiple frequency points and ensure sufficient frequency differences between adjacent frequency points, so that phase changes can be reliably measured; third, the electromagnetic response characteristics of different materials differ significantly within this frequency band, which is beneficial to improving the detection discrimination.

[0061] Regarding the frequency distribution characteristics, this embodiment strictly adheres to nonlinear, non-monotonic, and unequal-distance coding rules. On one hand, the output frequency difference between two adjacent frequency points within the set is a completely random value, with no fixed interval, completely abandoning the equidistant frequency hopping mode of traditional linear frequency sweeping. On the other hand, all frequency points are arranged randomly and disorderly within the set, without any monotonic trend of frequency increase or decrease, forming an irregular and unpredictable nonlinear frequency hopping excitation sequence. The implementation of this coded frequency point set makes the frequency hopping in the entire detection excitation process completely disordered, irregular, and unpredictable. The alternating magnetic field generated by the wireless charging transmitting coil is always in a dynamic jumping and non-steady-state switching state, making it impossible to form a fixed steady-state response mode. This innovative non-steady-state encoding excitation mode amplifies the difference in electromagnetic response between legitimate charging devices and metallic foreign objects to the extreme. Legitimate devices have a fixed electromagnetic structure and can maintain stable phase rotation inertia even in the face of disordered frequency jumps, resulting in a continuous and stable response. In contrast, metallic foreign objects lack a fixed coupled resonant structure and cannot form a stable electromagnetic response inertia. Each disordered frequency jump triggers the reconstruction, oscillation, and disorder of their internal eddy current field, causing violent and disordered fluctuations in phase rotation behavior. The dynamic response characteristics of the two are fundamentally different, completely solving the technical pain point of feature convergence and indistinguishability under traditional steady-state excitation. This provides clear and reliable physical feature support for subsequent feature parameter extraction and foreign object identification.

[0062] After determining the set of coded nonlinear frequency points, this embodiment excites the target micro-area on the wireless charging device according to the set of coded nonlinear frequency points. A micro-area refers to the wireless charging identification area on the wireless charging device. A device to be charged can only be reliably identified and efficiently charged when placed within this micro-area. For a multi-coil transmitting array, there are multiple micro-areas simultaneously, each corresponding to one or more transmitting coils. In this embodiment, the target micro-area refers to two scenarios: the first scenario is the micro-area triggered after an object is placed on the wireless charging device. That is, when a user places a device to be charged or a potential foreign object on the charging pad, the device identifies the location of the object through pressure sensors, capacitance sensors, or other detection methods, and determines the micro-area corresponding to that location as the target micro-area. The second scenario is the micro-area specified during periodic polling. That is, when no external object is detected, the wireless charging device automatically and alternately detects each micro-area at preset time intervals (e.g., every 30 seconds or every minute) to discover any foreign objects that may not have been actively triggered.

[0063] Exciting a target micro-area on a wireless charging device essentially involves applying an alternating current to the coil transmitting array of the wireless charging device, thereby generating an alternating magnetic field around it. This alternating magnetic field is the medium for energy transfer; when the receiving coil enters the range of this magnetic field, an electromotive force is induced, thereby generating a current to charge the device.

[0064] In this embodiment, the excitation process requires precise control of the excitation duration and amplitude at each frequency. The excitation duration at each frequency is within a preset time range, for example, 1.5 to 3.5 ms. This time range is designed based on the following considerations: if the excitation time is too short (e.g., less than 1 ms), the target micro-region may not have fully responded to the new frequency excitation, and the phase measurement value may still contain residual response from the previous frequency, leading to inaccurate measurements; if the excitation time is too long (e.g., greater than 4 ms), the target micro-region may have already fully established a steady-state response, and the transient response components will have decayed completely, failing to reflect the phase rotation inertia differences between different materials, and the excessively long excitation time will increase the total detection time and energy consumption. The duration range of 1.5 ms to 3.5 ms ensures that under excitation at each frequency, the target micro-region has enough time to generate a measurable response and retains sufficient transient characteristics for subsequent analysis. Specifically, the first 0.5ms after the excitation begins is considered the transient transition period, during which the system is adapting to the new excitation frequency and the electromagnetic field distribution is not yet stable; while the remaining time after 0.5ms is considered the frequency stabilization region, during which voltage and current are acquired and measured.

[0065] Regarding the excitation amplitude, the excitation amplitude for each frequency point is set between 3V and 6V, corresponding to an excitation energy of less than or equal to 0.5J. This safe amplitude range is set based on two considerations: Firstly, the excitation amplitude needs to be high enough to ensure the measurement signal-to-noise ratio, so that the measurement accuracy of the complex impedance meets the requirements of subsequent phase calculation and feature extraction. If the excitation amplitude is too low (e.g., less than 2V), the measurement signal may be too weak and easily affected by environmental electromagnetic noise, internal system electronic noise, and quantization noise, leading to increased phase calculation errors and affecting detection reliability. Secondly, the excitation amplitude must be strictly controlled to avoid heating risks. The eddy currents generated by a metallic foreign object in an alternating magnetic field are proportional to the magnetic field strength, which in turn is proportional to the excitation current (i.e., the excitation amplitude). If the excitation amplitude is too high or the excitation energy is too large, even with a short detection time, the metallic foreign object may experience a significant temperature rise. This not only violates the preventative purpose of foreign object detection (detecting the foreign object before it poses a danger) but may also cause thermal damage to the charging equipment itself or surrounding sensitive components. By limiting the excitation energy to less than 0.5J and combining it with a short excitation time, it can be ensured that even if there are metallic foreign objects, the temperature rise during the detection process is controlled within a safe range.

[0066] After exciting the target micro-region on the wireless charging device, this embodiment obtains the complex impedance of the target micro-region and calculates the phase for each frequency stable region, and summarizes them to obtain the phase sequence.

[0067] Specifically, for frequency point f i In this embodiment, the voltage V of the target micro-region is collected within its frequency stability region.i Current I i ; i represents the number of frequency points. Voltage acquisition is typically obtained from the transmitting coil terminals through a voltage divider circuit or a differential amplifier circuit, while current acquisition is obtained through a series sampling resistor or a current transformer. Furthermore, the sampling rate in this embodiment is greater than or equal to 1MHz to ensure phase accuracy. This high sampling rate requirement stems from the sensitivity of phase calculation to time resolution. The phase difference essentially reflects the time delay between voltage and current. If the sampling rate is too low (e.g., 100kHz), there are only about 10 sampling points per cycle, which introduces a large quantization error when calculating the phase using discrete sampling points. However, using a sampling rate of 1MHz or higher, more than 100 sampling points can be obtained per cycle, significantly improving the resolution of phase calculation. In addition, a high sampling rate helps capture high-frequency noise and transient disturbances in the signal, providing a sufficient data basis for subsequent filtering processing.

[0068] The acquired raw sampled values ​​need to be denoised using a bandpass filter. The bandpass filter effectively removes out-of-band noise (such as power supply interference and high-frequency switching noise) while preserving the main spectral components of the signal. After bandpass filtering, a three-point moving average is further applied to the sampled data. The three-point moving average is a simple and effective time-domain smoothing method. By averaging each sample point with its two preceding and following sample points, it can suppress random impulse noise and high-frequency spikes without significantly altering the signal's phase characteristics.

[0069] Subsequently, based on the voltage V of the target micro-region i Current I i Calculate the complex impedance Z(f) i The complex impedance is defined as the ratio of the voltage phasor to the current phasor, expressed by the following formula:

[0070] Z(f i ) =V i / I i ;

[0071] Based on the complex impedance Z(f) i Calculate the phase φ(f) i The formula is as follows:

[0072] φ(f i =arctan(Im(Z(f) i )) / Re(Z(f i )));

[0073] Among them, Im(Z(f) i )) represents the complex impedance Z(f i The imaginary part of Re(Z(f)); i )) represents the complex impedance Z(fi The real part of φ(f). Phase φ(f) i The physical meaning of phase angle (P) is the phase difference between voltage and current, reflecting the system's impedance angle. For a purely resistive load, the phase is zero; for an inductive load, the phase is positive (voltage leads current); for a capacitive load, the phase is negative (voltage lags current). In wireless charging devices, the transmitting coil itself has inductive characteristics, so the phase of the target micro-region is usually positive when unloaded. When the receiving device approaches, the equivalent impedance of the target micro-region changes due to mutual inductance and reflection impedance, and the phase changes accordingly. When a metallic foreign object is present, due to the equivalent resistance effect of eddy current losses and a slight change in inductance, the phase of the target micro-region will exhibit a different change pattern than that of a legitimate device.

[0074] Finally, the phases calculated under the stable regions of all frequencies are summarized to obtain the phase sequence. This phase sequence is the core input data for subsequent feature extraction and foreign object detection. To ensure data quality, this application also applies a frequency domain consistency check to the phase sequence. Specifically, it checks whether there are isolated outliers in the phase sequence, i.e., phase values ​​at a certain frequency that exhibit unreasonable jumps compared to the phase values ​​of their adjacent frequencies (e.g., jump amplitude exceeding a preset threshold, such as 30 degrees), and these jumps cannot be reasonably explained by changes in frequency intervals. If such isolated outliers exist, they are removed and replaced with interpolated results from adjacent normal points to avoid interference from anomalous data in subsequent feature calculations. This consistency check can effectively eliminate the influence of occasional measurement noise, electromagnetic interference pulses, or sampling errors, improving the reliability of the phase sequence.

[0075] Based on the acquired phase sequence, this embodiment further calculates the rotational stability index and modal perturbation index.

[0076] The rotational stability index quantifies the smoothness of the rotation of a phase sequence under coded nonlinear frequency excitation, reflecting the phase rotational inertial characteristics of the system. The calculation of this index involves two levels: first, the first-order phase rotational velocity is calculated, and then the rotational stability index is calculated.

[0077] The calculation of the rotational stability index based on the phase sequence includes:

[0078] The first-order phase rotational velocity Q(i) is calculated using the following formula:

[0079] Q(i)=(φ(f i+1 )-φ(f i )) / (f i+1 -f i );

[0080] Wherein, φ(f i ) represents the i-th frequency point f iThe measured phase; φ(f i+1 ) represents the (i+1)th frequency point f i+1 The measured phase; i represents the number of frequency points.

[0081] The first-order phase rotation velocity Q(i) represents the instantaneous rate of phase change with frequency. In traditional linear frequency scanning, if the impedance characteristics of a wireless charging device can be described by a simple lumped parameter model, the phase change with frequency usually exhibits a relatively regular trend, and the first-order phase rotation velocity may be approximately constant or change according to some predictable law. However, under the nonlinear frequency hopping excitation conditions of this embodiment, due to the unequal spacing and non-monotonic order of adjacent frequency points, the first-order phase rotation velocity exhibits a complex fluctuation pattern, and this fluctuation pattern is the key to distinguishing the dynamic response characteristics of different materials.

[0082] The rotational stability index Sθ is calculated using the following formula:

[0083] Sθ=Σ|Q(i+1)-Q(i)|;

[0084] Where Q(i+1) represents the (i+1)th frequency point f i+1 The first-order phase rotation velocity; Q(i) represents the i-th frequency point f i The first-order phase rotation speed.

[0085] The rotational stability index Sθ quantifies the total variation of the phase rotation velocity sequence. When the object on the wireless charging device is a legitimate device, the rotational velocity changes gradually due to the large phase rotational inertia, resulting in a small Sθ value that tends to be within a relatively constant range. However, when a metallic foreign object is present, the rotational velocity fluctuates violently due to the small phase rotational inertia, leading to a significant increase in the Sθ value. This significant difference provides a reliable basis for foreign object detection.

[0086] Compared to simple phase or impedance amplitude values, the rotational stability index Sθ utilizes not only phase information but also the dynamic law of phase variation with frequency. The rotational stability index Sθ is insensitive to changes in the absolute value of the measurement (for example, temperature changes and coil aging may cause an overall phase shift, but will not affect the rotational speed variation pattern), thus exhibiting good environmental robustness. Furthermore, due to the randomness of the coded nonlinear excitation, the distribution range of its rotational stability index remains relatively stable even with different types of metallic foreign objects or different models of legitimate equipment, facilitating the setting of a uniform detection threshold.

[0087] The modal perturbation index is another core characteristic parameter proposed in this application. It quantifies the deviation between the actual measured phase and the reference phase, reflecting the perturbation of the system's electromagnetic modes relative to the standard state. The index is calculated based on the difference between the phase sequence and a pre-established reference phase sequence.

[0088] The modal perturbation index is calculated based on the phase sequence and expressed by the following formula:

[0089] M=[ Σ (φ(f i )-φ ref (f i ))² ] 1 / 2 ;

[0090] Where M represents the modal perturbation index; φ(f i ) represents the i-th frequency point f i The measured phase; φ ref (f i ) represents the i-th frequency point f i The reference phase value. This definition is mathematically equivalent to the Euclidean distance (L2 norm) between two phase sequences, and physically represents the overall deviation between the actual electromagnetic response and the standard electromagnetic response.

[0091] During the initial calibration process, when a vehicle leaves the factory or is powered on for the first time, under no-load and standard receiver sample conditions, each micro-region (including the target micro-region) is excited according to a predetermined coding sequence Fref (including multiple frequency points). Complex impedance is then collected and a reference phase is calculated. The establishment of the reference phase is crucial for calibration. Due to manufacturing tolerances, component parameter variations, and assembly differences between different wireless charging devices, the inherent electromagnetic characteristics of each device differ. Factory calibration or initial power-on calibration establishes a personalized reference standard for each device and each micro-region, avoiding the impact of individual differences on detection performance. The calibration process is typically performed in a controlled environment, ensuring that environmental factors such as temperature and humidity are within standard ranges. A precisely calibrated standard receiver sample is used, possessing known electromagnetic parameters (such as coil inductance, resonant frequency, and equivalent resistance), representing the typical characteristics of a legitimate device.

[0092] The technical principle of the modal perturbation index is as follows:

[0093] When a legitimate receiving device is placed on the target micro-area, even if the device differs from the standard sample (e.g., different brands or models of mobile phones), its electromagnetic modes are still structurally similar to those of the standard sample: both have basic structures such as receiving coils, resonant compensation circuits, and rectifier circuits. Therefore, the overall trend and distribution characteristics of the phase sequence are quite close to the reference phase sequence, and the value of the mode disturbance index M is relatively small. This similarity stems from the fact that legitimate devices are designed in accordance with similar electromagnetic compatibility specifications and wireless charging standards, and their impedance characteristics are constrained within a certain range.

[0094] The situation changes fundamentally when a metallic foreign object is present in the target micro-region. The introduction of the metallic foreign object is equivalent to adding an additional impedance branch in parallel or series with the existing electromagnetic system. The characteristics of this branch are completely different from those of a legitimate device. The impedance of the metallic foreign object mainly consists of eddy current equivalent resistance and a weak equivalent inductance, and its frequency response characteristics are fundamentally different from those of an LC resonant network. Therefore, the measured phase sequence will exhibit a systematic deviation from the reference phase sequence: the phase may increase significantly at some frequencies and decrease significantly at others, presenting an overall distribution pattern inconsistent with the reference sequence. This deviation is reflected in the modal perturbation index as a significant increase in the M value.

[0095] Rotational stability index focuses on how the phase changes with frequency, while modal perturbation index focuses on the absolute deviation of the phase value from the standard state. Combining the two allows for a comprehensive characterization of the electromagnetic state of the target micro-region from both dynamic response characteristics and static modal deviation. Furthermore, the modal perturbation index is relatively insensitive to changes in the position of the foreign object (because the object's location within the micro-region will cause a deviation in the overall modes), while the rotational stability index is more sensitive to the material properties of the foreign object (due to significant differences in phase rotational inertia among different materials). The complementarity of these two indices further enhances the reliability of the detection.

[0096] After obtaining the rotational stability index and modal perturbation index, this embodiment can perform foreign object detection accordingly. Since the rotational stability index and modal perturbation index are two physical quantities with different dimensions and numerical ranges, direct numerical comparison or simple addition is unreasonable. Therefore, this embodiment first needs to normalize both, converting them to a unified numerical scale, and then construct a safety determination function through weighted fusion, including:

[0097] Construct a security decision function P safe :

[0098] P safe =w1·Sθ norm +w2·M norm ;

[0099] Wherein, Sθ norm M represents the normalized rotational stability index; norm w1 represents the normalized modal perturbation index; w2 represents the preset weight coefficients, which sum to 1.

[0100] Normalization can be achieved using various statistical methods, such as Min-Max normalization and Z-score standardization.

[0101] The choice of weighting coefficients reflects the assessment of the relative importance of the two feature parameters in the detection decision. In this embodiment, w1=0.55 and w2=0.45 are exemplarily chosen, which means that the rotational stability index plays a slightly dominant role in the judgment. The basis for this weighting allocation is that the rotational stability index directly reflects the difference in phase rotational inertia of the material, which is the essential physical characteristic that distinguishes legitimate equipment from metallic foreign objects, and has strong theoretical support and experimental verification; while the modal perturbation index can also effectively distinguish, its performance is affected by factors such as the accuracy of the reference phase calibration and environmental changes (such as temperature drift), and its stability is slightly inferior to that of the rotational stability index. Of course, in practical applications, the weighting coefficients can be adjusted and optimized according to specific application scenarios, types of detection objects, environmental conditions, etc., and can even be automatically learned through machine learning algorithms (such as support vector machines, neural networks, etc.) to find the optimal weight combination.

[0102] Safety decision function P safe The output value is a dimensionless numerical value between 0 and 1, with a larger value indicating a higher probability of the presence of a foreign object. Therefore, according to the safety determination function P... safe Function value, if P safe The function value is greater than or equal to the preset threshold P. th If P is present, it is determined that there is a foreign object in the current target micro-region, and power supply to that micro-region is refused; safe The function value is less than the preset threshold P th If the threshold Pth is not met, it is determined that no foreign object exists, and power can be supplied to the micro-area. The setting of the threshold Pth requires a trade-off between detection sensitivity and false alarm rate: if Pth is too low, the detection sensitivity is high, but it may misidentify normal, legitimate equipment as a foreign object; if Pth is too high, the false alarm rate is reduced, but it may miss some small or special-material metallic foreign objects. Typically, the setting of Pth is based on statistical analysis of a large amount of experimental data.

[0103] This safety decision function based on dual-feature weighted fusion improves the robustness of foreign object detection in this embodiment by fusing two complementary feature parameters. Abnormal fluctuations in a single feature will not lead to false positives because the other feature may still be within the normal range. Furthermore, the weighted fusion framework has good scalability; if new feature parameters need to be introduced in the future, only corresponding normalization terms and weight coefficients need to be added, without changing the overall decision framework.

[0104] In addition, this embodiment also performs spatial consistency checks based on the anomaly detection results of adjacent micro-areas. The basic assumption of the spatial consistency check is that the placement of metallic foreign objects on wireless charging devices usually has a certain physical size, and their influence range is often not strictly limited to a single micro-area, but may also have a detectable impact on adjacent micro-areas; conversely, some factors that cause anomalies in the detection of a single micro-area usually only affect that micro-area itself and will not affect adjacent micro-areas.

[0105] Specifically, the spatial consistency check in this embodiment includes: after detecting foreign objects in the current target micro-region and obtaining an abnormal result (i.e., Psafe ≥ Pth), further checking the detection results of adjacent micro-regions of the target micro-region. Adjacent micro-regions refer to other micro-regions that are physically adjacent to the target micro-region. If the detection result of the current target micro-region is abnormal, but the detection results of all its adjacent micro-regions are normal, it indicates that the abnormality may be an isolated local phenomenon, rather than caused by a spatially expandable metallic foreign object. In this case, the system adopts a strategy of increasing the threshold Pth to reduce false positives.

[0106] In practical applications, wireless charging devices may face various complex electromagnetic environments. For example, other nearby electronic devices, power adapters, metal table frames, etc., may introduce local electromagnetic interference. This interference may cause anomalies in the measurement data of a certain micro-area, but will not affect other micro-areas. However, this embodiment can effectively distinguish between global anomalies and local anomalies through spatial consistency checks, thereby significantly reducing the false alarm rate caused by local factors without reducing the sensitivity to real foreign objects.

[0107] To further reduce false alarms, the target micro-region needs to meet the requirement that the results of at least two consecutive independent detections are consistent, or, for multiple independent detections within a preset time window, the number of occurrences of the same detection result is greater than a preset threshold before the corresponding detection result is confirmed as valid.

[0108] The first approach requires that the target micro-area meet the requirement of consistent results from at least two consecutive independent detections. That is, two complete foreign object detection procedures are performed consecutively on the same target micro-area. If both detections determine it as abnormal (or both as normal), the detection result is confirmed as valid; if the two detection results are inconsistent (one abnormal and one normal), the detection continues. This double-confirmation mechanism can effectively eliminate misjudgments in a single detection caused by random factors such as occasional measurement noise and transient electromagnetic interference. Because each independent detection uses a different set of coded nonlinear frequency points, even if there is systematic interference at a specific frequency, it is difficult to produce the same misjudgment pattern under two different coding sequences.

[0109] The second approach involves multiple independent tests within a preset time window. A valid test result is only confirmed if the number of occurrences of the same result exceeds a preset threshold. For example, a 10-second time window is set, and five independent tests are performed within this window. At least four of these tests must produce the same result (e.g., four abnormal or four normal) to confirm the result. This approach is more lenient than the first and is suitable for scenarios with high testing frequency but requiring rapid response. The preset time window and threshold can be set according to the security level requirements of the application scenario: for high-security scenarios (such as in-vehicle wireless charging), stricter requirements can be adopted (e.g., at least two out of three tests within a 5-second time window must be identical); for general consumer scenarios (such as desktop wireless charging for mobile phones), more lenient requirements can be adopted (e.g., at least two out of three tests within a 10-second time window must be identical).

[0110] This embodiment also provides a wireless charging foreign object detection system, using the aforementioned wireless charging foreign object detection method, such as... Figure 2 As shown, the system includes:

[0111] Multi-coil transmitting array, encoding excitation control module, impedance acquisition module, phase calculation and dynamic analysis module, and decision controller;

[0112] The coding excitation control module is used to establish a set of coded nonlinear frequency points and to excite the target micro-region on the multi-coil transmitting array according to the set of coded nonlinear frequency points.

[0113] The impedance acquisition module is used to acquire the complex impedance of the target micro-region and calculate the phase in the stable region at each frequency point after excitation, and summarize them to obtain the phase sequence;

[0114] The phase calculation and dynamic analysis module is used to calculate the rotational stability index and modal perturbation index based on the phase sequence.

[0115] The determination controller is used to detect foreign objects based on the rotational stability index and the modal disturbance index.

[0116] The present invention has been described above by way of example with reference to the accompanying drawings. Obviously, the specific implementation of the present invention is not limited to the above-described manner. Any non-substantial improvements made using the inventive concept and technical solution; or the direct application of the inventive concept and technical solution to other situations without modification, are all within the protection scope of the present invention.

Claims

1. A method for detecting foreign objects in wireless charging devices, characterized in that, include: Establish a set of coded nonlinear frequency points; The target micro-region on the wireless charging device is excited according to the coded nonlinear frequency point set; In the stable region of each frequency point after excitation, the complex impedance of the target micro-region is obtained and the phase is calculated. The phase sequence is then obtained by summarizing the results. Calculate the rotational stability index and modal perturbation index based on the phase sequence; Foreign object detection is performed based on the rotational stability index and modal perturbation index.

2. The method for detecting foreign objects in wireless charging according to claim 1, characterized in that: In the coded nonlinear frequency point set, the output frequency of each frequency point is within a preset frequency range; the difference between the output frequencies of two adjacent frequency points is a random value; and the frequency points are arranged in a random order in the set.

3. The method for detecting foreign objects in wireless charging according to claim 1, characterized in that: The excitation duration of each frequency point is within a preset time range; the excitation amplitude of each frequency point is within a preset safe amplitude range.

4. The method for detecting foreign objects in wireless charging according to claim 1, characterized in that: The frequency stability region refers to the period of time remaining after the excitation has continued for a preset period of time for any frequency point.

5. The method for detecting foreign objects in wireless charging according to claim 1, characterized in that: The process of obtaining the complex impedance of the target micro-region and calculating its phase includes: For frequency point f i The voltage V of the target micro-region is collected within its frequency stability region. i Current I i ; i represents the number of frequency points; Calculate the complex impedance Z(f) i ): Z(f i ) =V i / I i ; According to the complex impedance Z(f) i Calculate the phase φ(f) i ): φ(f i )=arctan(Im(Z(f i )) / Re(Z(f i ))); Among them, Im(Z(f) i )) represents the complex impedance Z(f i The imaginary part of Re(Z(f)); i )) represents the complex impedance Z(f i The real part of ).

6. The method for detecting foreign objects in wireless charging according to claim 1, characterized in that: The rotational stability index is calculated based on the phase sequence, including: Calculate the first-order phase rotational velocity Q(i): Q(i)=(φ(f i+1 )-φ(f i )) / (f i+1 -f i ); Wherein, φ(f i ) represents the i-th frequency point f i The measured phase; φ(f i+1 ) represents the (i+1)th frequency point f i+1 The measured phase; i represents the number of frequency points; Calculate the rotational stability index Sθ: Sθ=Σ|Q(i+1)-Q(i)|; Where Q(i+1) represents the (i+1)th frequency point f i+1 The first-order phase rotation velocity; Q(i) represents the i-th frequency point f i The first-order phase rotation speed.

7. The method for detecting foreign objects in wireless charging according to claim 1, characterized in that: The modal perturbation index is calculated based on the phase sequence, including: M=[ Σ (φ(f i )-φ ref (f i ))² ] 1 / 2 ; Where M represents the modal perturbation index; φ(f i ) represents the i-th frequency point f i The measured phase; φ ref (f i ) represents the i-th frequency point f i The reference phase value.

8. The method for detecting foreign objects in wireless charging according to claim 1, characterized in that: Foreign object detection is performed based on the rotational stability index and modal perturbation index, including: Construct a security decision function P safe : P safe =w1·Sθ norm +w2·M norm ; Wherein, Sθ norm M represents the normalized rotational stability index; norm w1 represents the normalized modal perturbation index; w2 represents the preset weight coefficients, which sum to 1.

9. A method for detecting foreign objects in wireless charging according to claim 8, characterized in that: Foreign object detection is performed based on the rotational stability index and modal perturbation index, including: If the P safe The function value is greater than or equal to the preset threshold P. th If the condition is met, it is determined that there is a foreign object in the current target micro-region; otherwise, there is no foreign object.

10. A wireless charging foreign object detection system, using a wireless charging foreign object detection method according to any one of claims 1-9, characterized in that: The system includes: Multi-coil transmitting array, encoding excitation control module, impedance acquisition module, phase calculation and dynamic analysis module, and decision controller; The coding excitation control module is used to establish a set of coded nonlinear frequency points and to excite the target micro-region on the multi-coil transmitting array according to the set of coded nonlinear frequency points. The impedance acquisition module is used to acquire the complex impedance of the target micro-region and calculate the phase in the stable region at each frequency point after excitation, and summarize them to obtain the phase sequence; The phase calculation and dynamic analysis module is used to calculate the rotational stability index and modal perturbation index based on the phase sequence. The determination controller is used to detect foreign objects based on the rotational stability index and the modal disturbance index.

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