New energy automobile wireless charging efficiency optimization device and system

Abstract

The invention relates to the technical field of vehicle control, in particular to a new energy vehicle wireless charging efficiency optimization device and system.The device comprises a vehicle body, a receiving coil, a metal adsorption magnet, a ground layer, a transmitting coil, a connecting rod, a temperature sensor, a display screen and the system of the new energy vehicle wireless charging efficiency optimization device; the system of the new energy automobile wireless charging efficiency optimization device comprises a charging data acquisition module, a position alignment judgment module, a metal monitoring charging module and a charging mode optimization module. The target charging data is acquired, the real-time alignment state is acquired according to the target charging data, the charging mode is started, and the charging state is adjusted and optimized in real time according to the target charging data, so that the electric energy loss is reduced, and the charging efficiency is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of vehicle control, in particular to a new energy vehicle wireless charging efficiency optimization device and system. BACKGROUND

[0002] In recent years, new energy vehicle wireless charging technology is gradually moving from concept to practice, mainly divided into static and dynamic two types, relying on different physical principles to achieve energy transmission, static wireless charging, "stop and charge", especially suitable for short-term parking energy supplement, and no physical interface, avoiding the risk of plugging and electric shock, but the charging efficiency is low, the energy loss is about 6%~10% (current efficiency 90%~94%), lower than the wired charging of more than 95%, the charging efficiency is greatly affected by the environmental temperature, and the metal debris (such as screws) entering the magnetic field area will heat and reduce the efficiency, and therefore, an urgent need arises for a scheme to process magnetic field metal garbage and adjust the charging state according to the change of environmental temperature to improve the charging efficiency.

[0003] The Chinese patent with publication number CN106560974B discloses a wireless charging system and a wireless charging device, wherein the wireless charging system includes a primary side rectifier circuit, a voltage regulating circuit, an inverter circuit, a primary side coil and a primary side control circuit located on the infrastructure side, and the vehicle wireless charging system further includes a secondary side coil, a secondary side rectifier circuit and a secondary side control circuit located on the vehicle side; the primary side control circuit controls the primary side rectifier circuit to rectify the input alternating current into direct current, the voltage regulating circuit transforms the voltage of the direct current, the inverter circuit inverts the direct current into alternating current, which is transmitted to the primary side rectifier circuit through the primary side coil and the secondary side coil; the secondary side control circuit controls the secondary side rectifier circuit to rectify the alternating current into direct current and then output to the battery of the vehicle; the primary side control circuit and the secondary side control circuit transmit or receive signals through the primary side coil and the secondary side coil. It can be seen that this scheme still has the problems of not processing the magnetic field metal garbage and lacking adjustment of the charging state according to the change of environmental temperature, resulting in low charging efficiency. SUMMARY

[0004] Therefore, the present application provides a new energy vehicle wireless charging efficiency optimization device and system to overcome the problem of low charging efficiency caused by not processing the magnetic field metal garbage and lacking adjustment of the charging state according to the change of environmental temperature in the prior art.

[0005] To achieve the above-mentioned purpose, the present application provides a new energy vehicle wireless charging efficiency optimization device, which comprises: a metal adsorption magnet located inside the insulating layer for adsorbing metal garbage; an insulating layer placed outside the metal adsorption magnet and connected with the connecting body for blocking the influence of metal garbage on the device. The connector, which connects to the insulating layer, the transmitting coil, and the connecting rod, is used to carry the transmitting coil; The transmitting coil, which is placed inside the connector, is used to transmit charged energy; A connecting rod, one end of which is connected to the connecting body, and the end of which is away from the connecting body is connected to the temperature sensor; A temperature sensor, connected to the connecting rod and the display screen, is used to acquire the ambient temperature in the target charging data; The display screen, which is connected to the temperature sensor and the new energy vehicle wireless charging efficiency optimization device, is used to display the real-time alignment status and transmit the real-time alignment status to the vehicle system. The system of the wireless charging efficiency optimization device for new energy vehicles is connected to a display screen and to a temperature sensor via an internal connection cable (not shown in the figure) to acquire target charging data, and to activate the charging mode and optimize the charging efficiency in real time based on the target charging data.

[0006] On the other hand, the present invention also provides a system for optimizing the efficiency of wireless charging for new energy vehicles, the system comprising: The charging data acquisition module is used to acquire target charging data; The position alignment determination module is used to acquire the real-time alignment status based on the target charging data and update the real-time alignment status. The metal monitoring charging module is used to generate control data based on target charging data, and to activate the charging mode based on the control data. It is used to monitor metal waste in real time and adjust the charging mode based on the real-time monitoring results. The charging mode optimization module is used to update the charging mode according to the battery temperature and optimize the mode update process. It is also used to obtain the remaining charging time, correct the state update process according to the remaining charging time, optimize the state correction process, and optimize the features of the mode update and state correction processes.

[0007] Furthermore, the position alignment determination module includes: The status determination unit is used to acquire the real-time alignment status based on the target charging data and push the real-time alignment status to the display screen. A state update unit is used to update the real-time alignment state according to the offset distance, and the state update unit is connected to the state determination unit.

[0008] Further, the state determination unit obtains the real-time alignment state according to the target charging data, inputs the positioning data in the target charging data into the vector conversion model to obtain the positioning data vector output by the vector conversion model, inputs the positioning data vector into the alignment state determination model to obtain the alignment state value ao output by the alignment state determination model, compares the alignment state value ao with the preset alignment state value ao0, judges the compliance of the alignment state value according to the comparison result, and obtains the real-time alignment state according to the judgment result, wherein: When ao≥ao0, the state determination unit determines that the compliance of the alignment state value is up to standard, regards the alignment as the real-time alignment state, and pushes the real-time alignment state to the display screen and the car system; When ao<ao0, the state determination unit determines that the compliance of the alignment state value is not up to standard, regards the misalignment as the real-time alignment state, and pushes the real-time alignment state and the alignment coordinates to the display screen and the car system; When the vehicle body stops according to the alignment coordinates to obtain the parking state, the state determination unit inputs the positioning data vector into the parking state determination model to obtain the static alignment value aso output by the parking state determination model, compares the static alignment value aso with the preset static alignment value aso0, judges the compliance of the static alignment value according to the comparison result, and outputs the parking alignment state according to the judgment result, wherein: When aso≥aso0, the state determination unit determines that the compliance of the static alignment value is up to standard, regards the alignment as the parking alignment state for output; When aso<aso0, the state determination unit determines that the compliance of the static alignment value is not up to standard, regards the misalignment as the parking alignment state for output, and pushes the alignment coordinates to the display screen and the car system, and the vehicle body stops again according to the alignment coordinates until the compliance of the static alignment value is up to standard; The state updating unit updates the real-time alignment state according to the offset distance, calculates the offset distance ds according to the center coordinates (x1, y1, z1) of the receiving coil and the center coordinates (x2, y2, z2) of the transmitting coil, and sets , obtains the offset distance ds, compares the offset distance ds with the preset offset distance ds0, judges the state of the offset distance according to the comparison result, and updates the real-time alignment state according to the judgment result, wherein: When ds≥ds0, the state updating unit determines that the state of the offset distance is far distance, and does not update the real-time alignment state; When ds<ds0, the state updating unit determines that the state of the offset distance is near distance, updates the real-time alignment state, and directly determines the real-time alignment state as the alignment.

[0009] Further, the metal monitoring charging module generates control data according to target charging data, and opens the charging mode according to the control data, inputs the target charging data into the control data generation model, obtains the control data output by the control data generation model, and opens the charging mode according to the control data; The metal monitoring charging module monitors the metal garbage in real time, adjusts the charging mode according to the real-time monitoring result, compares the resonance frequency offset PM with the preset resonance frequency offset PM0, judges the state of the resonance frequency offset according to the comparison result, and outputs the real-time monitoring result according to the judgment result, wherein: When PM≤PM0, the metal monitoring charging module determines that the state of the resonance frequency offset is no offset, and outputs the non-existing metal garbage as the real-time monitoring result; When PM>PM0, the metal monitoring charging module determines that the state of the resonance frequency offset is offset, and outputs the existing metal garbage as the real-time monitoring result; When the metal monitoring charging module outputs the non-existing metal garbage as the real-time monitoring result, the charging mode is not adjusted; When the metal monitoring charging module outputs the existing metal garbage as the real-time monitoring result, the charging mode is adjusted: the charging mode is closed, and the metal adsorption magnet is controlled until the real-time monitoring result is non-existing metal garbage.

[0010] Further, the charging mode optimization module comprises: A temperature monitoring optimization unit is configured to update the charging mode according to the battery temperature in the target charging data, and to optimize the mode updating process according to the weather attribute; A time limit demand optimization unit is configured to obtain the remaining charging time according to the target charging data, to correct the state updating process according to the remaining charging time, and to optimize the state correction process according to the time of the electricity price peak value, and the time limit demand optimization unit is connected with the temperature monitoring optimization unit; A feature recognition optimization unit is configured to optimize the mode updating and state correction processes according to the ID feature recognition code, and the feature recognition optimization unit is connected with the time limit demand optimization unit.

[0011] Further, the temperature monitoring optimization unit updates the charging mode according to the battery temperature in the target charging data, compares the battery temperature DW with the first preset battery temperature DW1 and the second preset battery temperature DW2, judges the state of the battery temperature according to the comparison result, and updates the charging mode according to the judgment result, wherein: When DW≤DW1, the temperature monitoring optimization unit determines that the state of the battery temperature is low temperature, and updates the charging mode by adding the real-time preheating scheme to the charging mode; When DW1<DW≤DW2, the temperature monitoring optimization unit determines that the state of the battery temperature is moderate temperature, and does not update the charging mode; When DW>DW2, the temperature monitoring optimization unit determines that the state of the battery temperature is high temperature, and updates the charging mode by closing the charging mode; The temperature monitoring optimization unit optimizes the mode updating process according to the weather attribute, compares the environment temperature WH with the preset environment temperature WH0, judges the attribute of the environment temperature according to the comparison result, and outputs the weather attribute according to the judgment result, wherein: When WH≥WH0, the temperature monitoring optimization unit determines that the attribute of the environment temperature is normal low temperature, and outputs the non-cold day as the weather attribute; When WH<WH0, the temperature monitoring optimization unit determines that the attribute of the environment temperature is abnormal low temperature, and outputs the cold day as the weather attribute; The temperature monitoring optimization unit optimizes the mode updating process when the cold day is output as the weather attribute: when the state of the battery temperature is low temperature, the real-time preheating scheme is replaced by the pre-positioned preheating scheme, and the pre-positioned preheating scheme is added to the charging mode.

[0012] Further, the time limit optimization unit corrects the state updating process according to the remaining charging time, calculates the remaining charging time tp according to the remaining required power kp and the charging rate vp, sets tp=kp / vp, compares the remaining charging time tp with the preset remaining charging time tp0, judges the state of the remaining charging time according to the comparison result, and corrects the state updating process according to the judgment result, wherein: When tp≥tp0, the time limit optimization unit determines that the state of the remaining charging time is long time, and does not correct the state updating process; When tp<tp0, the time limit optimization unit determines that the state of the remaining charging time is short time, corrects the state updating process, cancels the state updating process, and expands the coil.

[0013] Further, the time requirement optimization unit optimizes the state according to the process of state correction, calculates the distance time T2 from the current time point td0 and the electricity price peak time point td2, and sets T2 = td2- td0; According to the distance time T2 of the electricity price peak and the charging rate vp, the chargeable amount dkp is calculated, dkp = T2 x vp, and the chargeable amount dkp is obtained. The chargeable amount dkp is compared with the remaining required power kp, the state of the chargeable amount is judged according to the comparison result, and the remaining charging time tp is optimized according to the judgment result, wherein: When dkp≥kp, the time requirement optimization unit determines that the state of the chargeable amount is coverable, and does not optimize the state of the remaining charging time tp; When dkp<kp, the time requirement optimization unit determines that the state of the chargeable amount is not coverable, calculates the chargeable amount difference ckm according to the chargeable amount dkp and the remaining required power kp, sets ckm = kp-dkp, and obtains the chargeable amount difference ckm. The chargeable amount difference ckm is pushed to the car system, and the car owner selects whether to continue charging after reaching the electricity price peak time point; When the car owner selects to continue charging after reaching the electricity price peak time point, the state of the remaining charging time tp is not optimized; When the car owner selects not to continue charging after reaching the electricity price peak time point, the state of the remaining charging time tp is optimized, and the remaining charging time tp is replaced by the distance time T2 of the electricity price peak.

[0014] Further, the feature recognition optimization unit optimizes the mode update and state correction process according to the ID feature recognition code, takes the preset ID feature recognition code as an index, constructs a temperature time habit database by taking the temperature use habit interval and time use habit corresponding to the preset ID feature recognition code as an associated result, obtains the temperature time habit database, compares the ID feature recognition code with the preset ID feature recognition code, and outputs the temperature use habit interval and time use habit according to the comparison result, wherein: When the ID feature recognition code is consistent with the preset ID feature recognition code, the temperature use habit interval and time use habit corresponding to the preset ID feature recognition code in the temperature time habit database are outputted; When the ID feature recognition code is inconsistent with the preset ID feature recognition code, the temperature use habit interval and time use habit are not outputted; The feature recognition optimization unit replaces the first preset ambient temperature WH1 and the second preset ambient temperature WH2 with a temperature use habit interval when the ID feature recognition code is consistent with a preset ID feature recognition code, and recompares the ambient temperature WH with the first preset ambient temperature WH1 and the second preset ambient temperature WH2. The preset remaining charging time length tp0 is replaced with a time limit use habit, and the remaining charging time length tp is recompared with the preset remaining charging time length tp0.

[0015] Compared with the prior art, the system of the present application has the beneficial effects that the target charging data is acquired, so as to subsequently optimize and improve the charging efficiency in real time according to the target charging data, the alignment state value is judged and adjusted in real time by the position alignment determination module, so as to save power and coil alignment time, the metal garbage is removed by the metal monitoring charging module, so as to avoid the influence of the metal garbage on the resonant system, cause the power loss, and start the charging mode to wirelessly charge the vehicle body, the charging mode optimization module is used to monitor the ambient temperature, judge the state of the distance time of the low valley of the electricity price and the state of the distance time of the peak of the electricity price, and adjust the charging state in real time according to the charging habit individual difference of different vehicle bodies, so as to reduce the influence of the charging efficiency in cold weather and save resources, thereby improving the wireless charging efficiency. BRIEF DESCRIPTION OF DRAWINGS

[0016] Figure 1 It is a structure schematic view of the new energy vehicle wireless charging efficiency optimization device of the present embodiment. Figure 2 It is a structure schematic view of the system of the new energy vehicle wireless charging efficiency optimization device of the present embodiment. Figure 3 It is a structure schematic view of the position alignment determination module of the present embodiment. Figure 4 It is a structure schematic view of the charging mode optimization module of the present embodiment. DETAILED DESCRIPTION

[0017] In order to make the purpose and advantages of the present application more clear and explicit, the present application will be further described below in combination with embodiments; it should be understood that the specific embodiments described herein are only used to explain the present application, and do not limit the present application.

[0018] The preferred embodiments of the present application will be described below with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are only used to explain the technical principles of the present application, and are not intended to limit the protection scope of the present application.

[0019] It should be noted that in the description of the present application, the terms indicating the direction or positional relationship of "upper", "lower", "left", "right", "inner", "outer" and the like are based on the direction or positional relationship shown in the drawings, which is only for the convenience of description, and does not indicate or imply that the device or element must have a particular orientation, be constructed and operated in a particular orientation, and therefore cannot be understood as a limitation of the present application.

[0020] In addition, it should be noted that in the description of the present application, unless otherwise explicitly specified and limited, the terms "mounting", "connecting", "connecting" should be understood broadly, for example, it can be fixedly connected, or it can be detachably connected, or integrally connected; it can be mechanically connected, or it can be electrically connected; it can be directly connected, or it can be indirectly connected through an intermediate medium; it can be the communication inside two elements. For those skilled in the art, the specific meaning of the above terms in the present application can be understood according to the specific circumstances.

[0021] Please refer to Figure 1 As shown in the structure schematic diagram of the new energy vehicle wireless charging efficiency optimization device of the present embodiment, the device comprises: The metal adsorption magnet 1 is located inside the insulating layer 2, and is used for adsorbing metal garbage; The insulating layer 2 is placed outside the metal adsorption magnet 1 and connected with the connecting body 3, and is used for blocking the influence of metal garbage on the device; The connecting body 3 is connected with the insulating layer 2, the transmitting coil 4 and the connecting rod 5, and is used for bearing the transmitting coil 4; The transmitting coil 4 is placed in the connecting body 3, and is used for transmitting charging energy; The connecting rod 5 is connected with the connecting body 3 at one end, and is connected with the temperature sensor 6 at the end away from the connecting body 3; The temperature sensor 6 is connected with the connecting rod 5 and the display screen 7, and is used for acquiring the environmental temperature in the target charging data; The display screen 7 is connected with the temperature sensor 6 and the system 8 of the new energy vehicle wireless charging efficiency optimization device, and is used for displaying the real-time alignment state and transmitting the real-time alignment state to the car system; The system 8 of the new energy vehicle wireless charging efficiency optimization device is connected with the display screen 7, and is connected with the temperature sensor 6 through the internal connecting line (not shown in the figure), and is used for acquiring the target charging data, and starting the charging mode according to the target charging data and optimizing the charging efficiency in real time.

[0022] Specifically, the new energy vehicle wireless charging efficiency optimization device is applied to new energy vehicle wireless charging terminals, such as wireless charging parking spaces. The device sets up a transmitting coil on the ground and a receiving coil on the vehicle body to wirelessly charge the vehicle body in a magnetic resonance manner. It also acquires the target charging data through a charging optimization processing system and optimizes the charging efficiency in real time based on the target charging data to save resources, reduce power loss, and thus improve the efficiency of wireless charging of the vehicle body.

[0023] Please see Figures 2 to 4 As shown, this is a schematic diagram of the system structure of the wireless charging efficiency optimization device for new energy vehicles in this embodiment. The system includes: The charging data acquisition module is used to acquire target charging data; The position alignment determination module is used to acquire the real-time alignment status based on the target charging data and update the real-time alignment status. The position alignment determination module is connected to the charging data acquisition module. The metal monitoring charging module is used to generate control data based on target charging data and to activate the charging mode based on the control data. It is used to monitor metal waste in real time and adjust the charging mode based on the real-time monitoring results. The metal monitoring charging module is connected to the position alignment determination module. The charging mode optimization module is used to update the charging mode according to the battery temperature and optimize the mode update process. It is also used to obtain the remaining charging time, correct the state update process according to the remaining charging time, optimize the state correction process, and optimize the features of the mode update and state correction processes. The charging mode optimization module is connected to the metal monitoring charging module.

[0024] Specifically, the system of the new energy vehicle wireless charging efficiency optimization device is applied to the new energy vehicle wireless charging efficiency optimization device. The system acquires target charging data, obtains real-time alignment status based on the target charging data, activates the charging mode, and adjusts and optimizes the charging status in real time based on the target charging data, thereby reducing power loss and improving charging efficiency. Specifically, the system acquires target charging data to facilitate real-time optimization and improvement of charging efficiency. The system also uses a position alignment judgment module to judge and adjust the alignment status value in real time to save power and coil alignment time. Furthermore, the system uses a metal monitoring charging module to remove metal debris, preventing metal debris from affecting the resonant system and causing power loss, and then activates the charging mode to wirelessly charge the vehicle. The system also uses a charging mode optimization module to monitor ambient temperature, judge the status of time between low and high electricity prices, and adjust the charging status in real time according to individual differences in charging habits of different vehicles, thereby reducing the impact of cold weather on charging efficiency and saving resources, thus improving wireless charging efficiency.

[0025] Specifically, the charging data acquisition module acquires the target charging data.

[0026] Specifically, the target charging data includes location data, ambient temperature, battery temperature, charging voltage, charging current, remaining required power, charging rate, and ID feature identification code. The location data refers to the data obtained by the vehicle body to locate the receiving coil. This embodiment does not limit the specific method of acquiring the location data; those skilled in the art can freely choose according to actual needs, such as acquiring the location data through vehicle GPS. The ambient temperature refers to the temperature of the surrounding environment when the vehicle body is charging; this embodiment acquires the ambient temperature through a temperature sensor. The charging voltage refers to the real-time voltage when the vehicle body is charging. The charging current refers to the real-time current when the vehicle body is charging; this embodiment acquires the charging voltage through a voltage sensor and the charging current through a current sensor. This embodiment does not limit the specific installation location of the voltage and current sensors; those skilled in the art can freely choose according to actual needs, such as connecting the voltage and current sensors to a temperature sensor. The remaining required power refers to the vehicle body's location data. The remaining power required for the vehicle to reach a fully charged state is specified. The charging rate refers to a numerical value used to measure the speed of vehicle charging. The battery temperature refers to the temperature of the vehicle's battery. This embodiment does not limit the specific methods for obtaining the remaining power required, charging rate, and battery temperature. For example, this embodiment obtains the remaining power required and charging rate from the vehicle's BMS via a wireless communication link. The wireless communication link refers to a signal channel for transmitting the remaining power required and charging rate. The vehicle BMS refers to a processor that controls the vehicle and stores vehicle-related data, such as the remaining power required and charging rate. The ID feature identification code refers to a QR code that provides a unique identity for the vehicle currently undergoing wireless charging. Different vehicles correspond to different ID feature identification codes, which are directly engraved on the vehicle by the car manufacturer. This embodiment does not limit the scanning method of the QR code containing the ID feature identification code. Those skilled in the art can freely choose according to actual needs. For example, this embodiment uses radio waves for scanning.

[0027] Specifically, the charging data acquisition module acquires target charging data so that charging efficiency can be optimized and improved in real time based on the target charging data.

[0028] Specifically, the position alignment determination module includes: The status determination unit is used to acquire the real-time alignment status based on the target charging data and push the real-time alignment status to the display screen. A state update unit is used to update the real-time alignment state according to the offset distance, and the state update unit is connected to the state determination unit.

[0029] Specifically, the position alignment determination module judges the alignment status value through the status determination unit so as to adjust the vehicle body according to the real-time alignment status. The position alignment determination module also directly determines the alignment status as aligned by the offset range supported by the coil, so as to save power and coil alignment time, thereby improving the efficiency of wireless charging.

[0030] Specifically, the state determination unit acquires the real-time alignment state based on the target charging data, inputs the positioning data from the target charging data into a vector conversion model to obtain the positioning data vector output by the vector conversion model, inputs the positioning data vector into the alignment state determination model to obtain the alignment state value ao output by the alignment state determination model, compares the alignment state value ao with the preset alignment state value ao0, determines the compliance of the alignment state value based on the comparison result, and acquires the real-time alignment state based on the determination result, wherein: When ao≥ao0, the state determination unit determines that the alignment status value meets the standard, takes the alignment as the real-time alignment status, and pushes the real-time alignment status to the display screen and the vehicle system. When ao < ao0, the state determination unit determines that the alignment status value does not meet the standard, takes the unaligned state as the real-time alignment state, and pushes the real-time alignment status and alignment coordinates to the display screen and the vehicle system. When the vehicle stops according to the alignment coordinates and obtains the stopping state, the positioning data vector is input into the stopping state determination model, and the stopping state determination model outputs a static alignment value aso. The static alignment value aso is compared with a preset static alignment value aso0. Based on the comparison result, the compliance of the static alignment value is judged, and the stopping alignment state is output based on the judgment result. When aso≥aso0, the state determination unit determines that the static alignment value meets the standard and outputs the aligned value as the parking alignment state. When aso < aso0, the state determination unit determines that the static alignment value does not meet the standard, outputs the unaligned state as the parking alignment state, and pushes the alignment coordinates to the display screen and the vehicle system. The vehicle body re-parks according to the alignment coordinates until the static alignment value meets the standard.

[0031] Specifically, the vector transformation model refers to a fusion deep learning model that uses location data as input data and location data vectors as output data. This embodiment does not limit the specific construction method of the vector transformation model; those skilled in the art can freely choose according to actual needs. For example, convolutional neural networks and multilayer perceptrons can be used as data processing branches of the fusion deep learning model, and historical location data and their corresponding location data vectors can be used as a training set to train the fusion deep learning model to obtain the vector transformation model. The location data vector refers to the numerical value describing the features of the location data obtained according to the vector transformation model. The alignment state determination model refers to using the location data vector as input data and the alignment state value as output data. This embodiment does not limit the specific construction method of the alignment state determination model. Those skilled in the art can freely choose according to actual needs. For example, the recurrent neural network model can be trained by using historical positioning data vectors and their corresponding alignment state values ​​as a training set to obtain the alignment state determination model. The alignment state value refers to the numerical value obtained from the alignment state determination model that reflects the degree of alignment between the transmitting coil and the receiving coil. The preset alignment state value refers to the preset value used to judge the compliance of the alignment state value. This embodiment does not limit the specific value setting of the preset alignment state value ao0. Those skilled in the art can freely choose according to actual needs. For example, in this embodiment, ao0 is set to 0 based on historical experience.9. The compliance status of the alignment state value refers to the degree of compliance of the alignment state value judged based on the alignment state value and the preset alignment state value. The compliance status of the alignment state value includes compliance and non-compliance. This embodiment does not limit the specific method of pushing the real-time alignment status to the display screen. Those skilled in the art can freely choose according to actual needs, such as pushing the real-time alignment status to the display screen through wireless network and Bluetooth. The alignment coordinates refer to the coordinate values ​​that guide the charging coil and transmitting coil of the vehicle body to align for normal charging. This embodiment does not limit the specific method of obtaining the alignment coordinates. Those skilled in the art can freely choose according to actual needs, such as obtaining them through the vehicle's LiDAR. The parking state determination model refers to a recurrent neural network model that takes the positioning data vector as input data and the static alignment value as output data. This embodiment does not limit the specific method of obtaining the parking state determination model. The specific construction method of the model is not limited, and those skilled in the art can freely choose according to actual needs. For example, the historical positioning data vector and its corresponding static alignment value can be used as a training set to train a recurrent neural network model to obtain a parking state determination model. The static alignment value refers to the value obtained from the parking state determination model that reflects the degree of alignment between the transmitting coil and the receiving coil in the parking state. The preset static alignment value refers to a preset value for judging the compliance of the static alignment value. This embodiment does not limit the specific value of the preset static alignment value aso0, and those skilled in the art can freely choose according to actual needs. For example, in this embodiment, aso0 is set to 0.95. The compliance of the static alignment value refers to the degree of compliance of the static alignment value judged based on the static alignment value and the preset static alignment value. The compliance of the static alignment value includes compliance and non-compliance.

[0032] Specifically, the status determination unit judges whether the alignment status value meets the standard and pushes the real-time alignment status to the display screen so that the vehicle body can be adjusted according to the real-time alignment status to ensure charging efficiency.

[0033] Specifically, the state update unit updates the real-time alignment state based on the offset distance, calculates the offset distance ds based on the center coordinates (x1, y1, z1) of the receiving coil and the center coordinates (x2, y2, z2) of the transmitting coil, and sets... The offset distance ds is obtained, and the offset distance ds is compared with the preset offset distance ds0. The state of the offset distance is judged according to the comparison result, and the real-time alignment state is updated according to the judgment result, wherein: When ds≥ds0, the state update unit determines the offset distance as a long distance and does not update the real-time alignment state. When ds < ds0, the state update unit determines that the offset distance is close, updates the real-time alignment state, and directly determines that the real-time alignment state is aligned.

[0034] Specifically, the center coordinates of the receiving coil refer to the coordinates of the center point of the receiving coil, and the center coordinates of the transmitting coil refer to the coordinates of the center point of the transmitting coil. Here, x1 represents the value of the center coordinates of the receiving coil on the x-axis of the three-dimensional spatial coordinate system, y1 represents the value of the center coordinates of the receiving coil on the y-axis of the three-dimensional spatial coordinate system, z1 represents the value of the center coordinates of the receiving coil on the z-axis of the three-dimensional spatial coordinate system, x2 represents the value of the center coordinates of the transmitting coil on the x-axis of the three-dimensional spatial coordinate system, y2 represents the value of the center coordinates of the transmitting coil on the y-axis of the three-dimensional spatial coordinate system, and z2 represents the value of the center coordinates of the transmitting coil on the z-axis of the three-dimensional spatial coordinate system. This embodiment does not limit the specific construction method of the three-dimensional spatial coordinate system; those skilled in the art can refer to this description. The specific method for obtaining the center coordinates of the receiving coil and the transmitting coil can be freely chosen according to actual needs. For example, the center of gravity of the vehicle can be used as the origin to construct a three-dimensional coordinate system. This embodiment does not limit the specific method for obtaining the center coordinates of the receiving coil and the transmitting coil. Those skilled in the art can freely choose according to actual needs. For example, the center coordinates of the receiving coil and the transmitting coil can be obtained by installing an ultra-wideband positioning base station at the center coordinate of the transmitting coil and an ultra-wideband positioning tag at the center coordinate of the receiving coil. The preset offset distance refers to a preset value for judging the state of the offset distance. This embodiment does not limit the specific value of the preset offset distance ds0. For example, this embodiment uses a D4Q coil, and sets ds0=300mm according to the offset range supported by the D4Q coil. The D4Q coil refers to a coil that can still maintain normal charging of the vehicle body within the preset offset distance. The state of the offset distance refers to the degree of distance between the offset distance and the preset offset distance. The state of the offset distance includes long distance and short distance.

[0035] Specifically, the state update unit determines the state of the offset distance. When the offset distance is close, the alignment state is directly determined as aligned based on the offset range supported by the coil, so as to save power and coil alignment time, thereby improving the efficiency of wireless charging.

[0036] Specifically, the metal monitoring charging module generates control data based on the target charging data, and activates the charging mode based on the control data. The target charging data is input into the control data generation model to obtain the control data output by the control data generation model. The metal monitoring charging module then activates the charging mode based on the control data.

[0037] Specifically, the control data generation model refers to a recurrent neural network model that uses target charging data as input data and control data as output data. This embodiment does not limit the specific construction method of the control data generation model. Those skilled in the art can freely choose according to actual needs. For example, the recurrent neural network model can be trained using historical target charging data and its corresponding control data as a training set to obtain the control data generation model. The control data refers to the signal obtained from the control data generation model to enable the charging mode. This embodiment does not limit the specific control method for enabling the charging mode based on the control data. Those skilled in the art can freely choose according to actual needs. For example, the power switch of the charging circuit can be controlled by inputting the control data into a relay to enable and disable the charging mode. The charging mode refers to the mode in which the transmitting coil and receiving coil form magnetic resonance to charge the vehicle body according to the control signal.

[0038] Specifically, the metal monitoring and charging module controls the metal adsorption magnet by generating control data to remove metal debris, thus preventing the presence of metal debris from affecting the resonant system and causing power loss. It also activates the charging mode to wirelessly charge the vehicle body, thereby improving the efficiency of wireless charging.

[0039] Specifically, the metal monitoring charging module monitors metal waste in real time and adjusts the charging mode based on the real-time monitoring results. It compares the resonant frequency offset PM with a preset resonant frequency offset PM0, determines the state of the resonant frequency offset based on the comparison result, and outputs the real-time monitoring results based on the determination result. When PM≤PM0, the metal monitoring charging module determines that the resonant frequency offset is zero and outputs the absence of metal waste as the real-time monitoring result. When PM > PM0, the metal monitoring charging module determines that the resonant frequency offset is offset and outputs the presence of metal waste as a real-time monitoring result. When the metal monitoring charging module outputs the absence of metal waste as a real-time monitoring result, it does not adjust the charging mode. When the metal monitoring and charging module outputs the presence of metal waste as a real-time monitoring result, it adjusts the charging mode: turning off the charging mode and controlling the metal adsorption magnet until the real-time monitoring result shows that there is no metal waste.

[0040] Specifically, the resonant frequency offset refers to the difference between the actual resonant frequency and the inherent resonant frequency. The actual resonant frequency refers to the resonant frequency of the resonant system under external interference, while the inherent resonant frequency refers to the resonant frequency of the resonant system in the absence of external interference. The resonant system refers to the energy system formed by the vibration of the transmitting and receiving coils for energy transfer. The resonant frequency refers to the specific frequency at which the energy conversion efficiency of the resonant system is highest during vibration. This embodiment does not limit the specific method for obtaining the resonant frequency offset; those skilled in the art can freely choose according to actual needs, such as obtaining the resonant frequency offset by connecting a detection circuit in series in the transmitting coil. The preset resonant frequency offset refers to... The preset value for judging the state of the resonant frequency offset is not limited in this embodiment. Those skilled in the art can freely choose according to actual needs. For example, in this embodiment, PM0 is set to 95kHz based on the test of the stability limit of the resonant system. The state of the resonant frequency offset refers to whether there is a deviation in the resonant frequency offset determined by the difference between the resonant frequency offset and the preset resonant frequency offset. The state of the resonant frequency offset includes no offset and offset. The specific method of controlling the metal adsorption magnet is not limited in this embodiment. Those skilled in the art can freely choose according to actual needs. For example, the metal adsorption magnet can be controlled by a PID control algorithm.

[0041] Specifically, the metal monitoring charging module judges the state of the resonant frequency offset to monitor in real time whether there is metal debris in the resonant system. When the real-time monitoring result shows that there is metal debris, the charging mode is turned off in time, and the metal adsorption magnet is controlled to adsorb the metal debris, thereby saving energy, reducing energy loss, and improving charging efficiency.

[0042] Specifically, the charging mode optimization module includes: The temperature monitoring and optimization unit is used to update the charging mode based on the battery temperature in the target charging data, and also to optimize the mode update process based on weather attributes. The timeliness demand optimization unit is used to obtain the remaining charging time, correct the state update process based on the remaining charging time, and optimize the state correction process based on the time between the peak electricity price and the peak electricity price. The timeliness demand optimization unit is connected to the temperature monitoring optimization unit. The feature recognition optimization unit is used to optimize the process of pattern update and state correction based on the ID feature identification code. The feature recognition optimization unit is connected to the timeliness requirement optimization unit.

[0043] Specifically, the charging mode optimization module monitors the ambient temperature to reduce the impact of cold weather on charging efficiency, thereby reducing energy loss. The module also uses a timeliness demand optimization unit to assess the time elapsed between low and high electricity prices to adjust the charging rate and conserve resources. Furthermore, the module employs a feature recognition optimization unit to adjust the charging status in real time based on individual differences in charging habits across different vehicles, thereby improving wireless charging efficiency.

[0044] Specifically, the temperature monitoring and optimization unit updates the charging mode based on the battery temperature in the target charging data, compares the battery temperature DW with a first preset battery temperature DW1 and a second preset battery temperature DW2, determines the state of the battery temperature based on the comparison result, and updates the charging mode based on the determination result, wherein: When DW≤DW1, the temperature monitoring and optimization unit determines that the battery temperature is low and updates the charging mode by adding a real-time preheating scheme to the charging mode. When DW1 < DW ≤ DW2, the temperature monitoring and optimization unit determines that the battery temperature is moderate and does not update the charging mode. When DW > DW2, the temperature monitoring and optimization unit determines that the battery temperature is high and updates the charging mode by turning off the charging mode.

[0045] Specifically, the first preset battery temperature DW1 refers to the lower limit of the preset value for judging the state of the battery temperature, and the second preset battery temperature DW2 refers to the upper limit of the preset value for judging the state of the battery temperature. This embodiment does not limit the specific values ​​of the first preset battery temperature DW1 and the second preset battery temperature DW2. Those skilled in the art can freely choose according to actual needs. For example, in this embodiment, DW1 is set to 0°C and DW2 to 35°C based on historical experience regarding the relationship between battery temperature and charging efficiency. The state of the battery temperature refers to the degree of high or low battery temperature judged from the first preset battery temperature and the second preset battery temperature. The state of the battery temperature includes low temperature, moderate temperature and high temperature. Real-time preheating refers to the operation of heating the vehicle battery during the charging process. This embodiment does not limit the specific method of real-time preheating. Those skilled in the art can freely choose according to actual needs. For example, real-time preheating can be performed through a PTC heater. The PTC heater refers to the heating element for real-time preheating.

[0046] Specifically, the temperature monitoring and optimization unit determines the ambient temperature. When the ambient temperature is low, it preheats the charging mode in real time to reduce the impact of low temperature on charging efficiency. When the ambient temperature is high, it shuts down the charging mode to avoid irreversible damage to the battery, charging system, and vehicle safety caused by high temperature, thereby improving the safety and charging efficiency of wireless charging.

[0047] Specifically, the temperature monitoring optimization unit optimizes the model update process based on weather attributes, compares the ambient temperature WH with the preset ambient temperature WH0, determines the attributes of the ambient temperature based on the comparison result, and outputs the weather attributes based on the determination result, wherein: When WH≥WH0, the temperature monitoring optimization unit determines that the ambient temperature is normal low temperature and outputs non-cold weather as the weather attribute. When WH < WH0, the temperature monitoring optimization unit determines that the ambient temperature is abnormally low and outputs cold weather as a weather attribute. The temperature monitoring optimization unit optimizes the mode update process when outputting cold weather as a weather attribute: when the battery temperature is low, the real-time preheating scheme is replaced with a preheating scheme, and the preheating scheme is added to the charging mode.

[0048] Specifically, the preset ambient temperature refers to a preset value for judging the properties of the ambient temperature. This embodiment does not limit the specific value of the preset ambient temperature WH0. Those skilled in the art can freely choose according to actual needs, as long as the requirement of WH0 < WH1 is met. For example, in this embodiment, WH0 is set to -10℃ based on the average temperature of cold weather. The properties of the ambient temperature refer to the degree of normal low temperature of the ambient temperature judged based on the ambient temperature and the preset ambient temperature. The properties of the ambient temperature include normal low temperature and abnormal low temperature. The preheating refers to the operation of heating the transmitting coil, receiving coil and vehicle battery before the charging mode is turned on. This embodiment does not limit the specific method of preheating. Those skilled in the art can freely choose according to actual needs, such as using a PTC heater for preheating.

[0049] Specifically, the temperature monitoring and optimization unit determines the properties of the ambient temperature. When the ambient temperature is abnormally low, it preheats the environment in advance to reduce the impact of cold weather on charging efficiency, thereby reducing energy loss and ensuring charging efficiency in cold weather.

[0050] Specifically, the timeliness requirement optimization unit performs state correction during the state update process based on the remaining charging time. It calculates the remaining charging time tp based on the remaining required power kp and the charging rate vp, setting tp = kp / vp to obtain the remaining charging time tp. The remaining charging time tp is then compared with a preset remaining charging time tp0. Based on the comparison result, the state of the remaining charging time is determined, and the state update process is corrected based on the determination result. Wherein: When tp≥tp0, the timeliness requirement optimization unit determines the remaining charging time as a long time and does not perform state correction during the state update process. When tp < tp0, the timeliness requirement optimization unit determines that the remaining charging time is short, corrects the state update process, cancels the state update process, and expands the coil.

[0051] Specifically, the preset remaining charging time refers to a preset value for judging the state of the remaining charging time. This embodiment does not limit the specific value of the preset remaining charging time tp0. Those skilled in the art can freely choose according to actual needs. For example, in this embodiment, the charging efficiency is statistically analyzed based on experiments to set tp0=1.5h. The state of the remaining charging time refers to the length of the remaining charging time judged based on the remaining charging time and the preset remaining charging time. The state of the remaining charging time includes long time and short time. The expanding coil refers to the technical means of expanding the energy transmission range of the transmitting coil, such as using an array of multiple coils to expand the energy transmission range.

[0052] Specifically, the timeliness requirement optimization unit determines the state of the remaining charging time. When the state of the remaining charging time is short, it does not determine the state of the offset distance, but directly performs coil adaptive adjustment to save the alignment time of the transmitting coil and the receiving coil, thereby quickly improving charging efficiency in a short time and reducing energy consumption.

[0053] Specifically, the timeliness demand optimization unit optimizes the state according to the process of state correction based on the time difference between the peak electricity price and the peak electricity price. It calculates the time difference between the peak electricity price and the peak electricity price based on the current time point td0 and the peak electricity price time point td2, and sets T2 = td2 - td0. The rechargeable amount dkp is calculated based on the peak electricity price distance time T2 and the charging rate vp, where dkp = T2 × vp. The rechargeable amount dkp is then compared with the remaining required electricity kp. Based on the comparison result, the status of the rechargeable amount is determined, and the status of the remaining charging time tp is optimized according to the determination result. Where: When dkp≥kp, the timeliness requirement optimization unit determines that the state of the rechargeable amount is coverable and does not optimize the state of the remaining charging time tp. When dkp < kp, the timeliness demand optimization unit determines that the rechargeable amount is not covered. It calculates the rechargeable amount difference ckm based on the rechargeable amount dkp and the remaining required amount kp, sets ckm = kp - dkp, obtains the rechargeable amount difference ckm, and pushes the rechargeable amount difference ckm to the vehicle system, so that the car owner can choose whether to continue charging after reaching the peak electricity price time. When a car owner chooses to continue charging after reaching the peak electricity price time, the remaining charging time tp status is not optimized. When a car owner chooses not to continue charging after reaching the peak electricity price time, the remaining charging time tp is optimized by replacing the remaining charging time tp with the distance time from the peak electricity price T2.

[0054] Specifically, the current time point refers to the time when charging of the vehicle body begins. This embodiment does not limit the specific method of obtaining the current time point; those skilled in the art can freely choose according to actual needs, such as obtaining it through the vehicle's BMS. The peak electricity price time point refers to the time when the charging electricity price begins to reach its highest value during the day. This embodiment does not limit the specific method of obtaining the peak electricity price time point; those skilled in the art can freely choose according to actual needs, such as querying the peak electricity price time point through the official website of the State Grid Corporation of their province or city. The preset peak electricity price distance time refers to a preset value for judging the state of the peak electricity price distance time. This embodiment does not limit the specific method of obtaining the peak electricity price distance time. The specific value of the peak electricity price distance time T20 is limited, and those skilled in the art can freely choose it according to actual needs. For example, in this embodiment, T20 is set to 50 minutes based on historical experience. The state of the peak electricity price distance time refers to the length of the peak electricity price distance time judged by the comparison with the preset peak electricity price distance time. The state of the peak electricity price distance time includes long time and short time. The state of the rechargeable amount refers to the coverage of the rechargeable amount with the remaining required amount of electricity judged by the comparison with the remaining required amount of electricity. The state of the rechargeable amount includes coverage and non-coverage. The vehicle owner refers to the user of the new energy vehicle that is wirelessly charged.

[0055] Specifically, the timeliness demand optimization unit determines the time between low and high electricity prices. When the time between high and low electricity prices is short, the charging rate is rapidly increased by a second state optimization coefficient that increases from 1.24 to 1.46. The constant term 1.46 of the second state optimization coefficient is the maximum value that the second state optimization coefficient can reach, and the constant coefficient 0.22 represents the magnitude of change of the second state optimization coefficient. This is to accelerate charging before the arrival of the electricity price peak, save resources, and thus improve the adaptability of charging efficiency.

[0056] Specifically, the feature recognition optimization unit performs feature optimization on the process of pattern update and state correction based on the ID feature recognition code. It uses a preset ID feature recognition code as an index and constructs a temperature and time-of-use habit database using the temperature usage habit range and time-of-use habit corresponding to the preset ID feature recognition code as association results. The unit then compares the ID feature recognition code with the preset ID feature recognition code and outputs the temperature usage habit range and time-of-use habit based on the comparison result. When the ID feature identification code matches the preset ID feature identification code, the temperature usage habit range and time usage habit corresponding to the preset ID feature identification code will be output from the temperature time-effect habit database; When the ID feature identification code is inconsistent with the preset ID feature identification code, the temperature usage range and time-of-use usage will not be output; When the ID feature identification code matches the preset ID feature identification code, the feature recognition optimization unit replaces the first preset ambient temperature WH1 and the second preset ambient temperature WH2 with the temperature usage habit range, and re-compares the ambient temperature WH with the first preset ambient temperature WH1 and the second preset ambient temperature WH2. Replace the preset remaining charging time tp0 with the usage habits of the time period, and compare the remaining charging time tp with the preset remaining charging time tp0 again.

[0057] Specifically, the preset ID feature identification code refers to a preset index that stores historical preset ID feature identification codes and retrieves the temperature usage habit range and time-based usage habit corresponding to the preset ID feature identification code. The temperature usage habit range refers to the temperature range where the vehicle body has the highest charging efficiency in wireless charging, and the time-based usage habit refers to the remaining charging time when the vehicle body has the highest charging efficiency in wireless charging. The temperature and time-based usage habit database refers to a data retrieval library that uses the preset ID feature identification code as an index and uses the temperature usage habit range and time-based usage habit corresponding to the preset ID feature identification code as the association results. The ID feature identification code being consistent with the preset ID feature identification code means that the ID feature identification code and the preset ID feature identification code have the same graphic. The ID feature identification code being inconsistent with the preset ID feature identification code means that the ID feature identification code and the preset ID feature identification code have different graphic.

[0058] Specifically, the feature recognition optimization unit compares the ID feature identification code with the preset ID feature identification code in the temperature time-related habit database to obtain the temperature usage habit range and time-related usage habit, and optimizes the pattern update and state correction process accordingly. This allows for real-time adjustment of the charging state based on individual differences in charging habits of different vehicle bodies, thereby improving wireless charging efficiency.

[0059] The technical solution of the present invention has been described above with reference to the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will all fall within the scope of protection of the present invention.

Claims

1. A wireless charging efficiency optimization device for new energy vehicles, characterized in that, The device includes: Metal magnets, located inside an insulating layer, are used to attract metal waste. An insulating layer, placed outside the metal adsorption magnet and connected to the connector, is used to block the impact of metal waste on the wireless charging efficiency optimization device for new energy vehicles. The connector, which connects to the insulating layer, the transmitting coil, and the connecting rod, is used to carry the transmitting coil; The transmitting coil, which is placed inside the connector, is used to transmit charged energy; A connecting rod, one end of which is connected to the connecting body, and the end of which is away from the connecting body is connected to the temperature sensor; A temperature sensor, connected to the connecting rod and the display screen, is used to acquire the ambient temperature in the target charging data; The display screen, which is connected to the temperature sensor and the new energy vehicle wireless charging efficiency optimization device, is used to display the real-time alignment status and transmit the real-time alignment status to the vehicle system. The system of the wireless charging efficiency optimization device for new energy vehicles is connected to a display screen and to a temperature sensor via an internal connection cable (not shown in the figure) to acquire target charging data, and to activate the charging mode and optimize the charging efficiency in real time based on the target charging data.

2. A system applied to the wireless charging efficiency optimization device for new energy vehicles as described in claim 1, characterized in that, The system includes: The charging data acquisition module is used to acquire target charging data; The position alignment determination module is used to acquire the real-time alignment status based on the target charging data and update the real-time alignment status. The metal monitoring charging module is used to generate control data based on target charging data, and to activate the charging mode based on the control data. It is used to monitor metal waste in real time and adjust the charging mode based on the real-time monitoring results. The charging mode optimization module is used to update the charging mode according to the battery temperature and optimize the mode update process. It is also used to obtain the remaining charging time, correct the state update process according to the remaining charging time, optimize the state correction process, and optimize the features of the mode update and state correction processes.

3. The system of the new energy vehicle wireless charging efficiency optimization device according to claim 2, characterized in that, The position alignment determination module includes: The status determination unit is used to acquire the real-time alignment status based on the target charging data and push the real-time alignment status to the display screen. A state update unit is used to update the real-time alignment state according to the offset distance, and the state update unit is connected to the state determination unit.

4. The system of the new energy vehicle wireless charging efficiency optimization device according to claim 3, characterized in that, The state determination unit acquires the real-time alignment state based on the target charging data, inputs the positioning data from the target charging data into a vector conversion model to obtain the positioning data vector output by the vector conversion model, inputs the positioning data vector into the alignment state determination model to obtain the alignment state value ao output by the alignment state determination model, compares the alignment state value ao with the preset alignment state value ao0, judges the compliance of the alignment state value based on the comparison result, and acquires the real-time alignment state based on the judgment result, wherein: When ao≥ao0, the state determination unit determines that the alignment status value meets the standard, takes the alignment as the real-time alignment status, and pushes the real-time alignment status to the display screen and the vehicle system. When ao < ao0, the state determination unit determines that the alignment status value does not meet the standard, takes the unaligned state as the real-time alignment state, and pushes the real-time alignment status and alignment coordinates to the display screen and the vehicle system. When the vehicle stops according to the alignment coordinates and obtains the stopping state, the positioning data vector is input into the stopping state determination model, and the stopping state determination model outputs a static alignment value aso. The static alignment value aso is compared with a preset static alignment value aso0. Based on the comparison result, the compliance of the static alignment value is judged, and the stopping alignment state is output based on the judgment result. When aso≥aso0, the state determination unit determines that the static alignment value meets the standard and outputs the aligned value as the parking alignment state. When aso < aso0, the state determination unit determines that the static alignment value does not meet the standard, outputs the unaligned state as the parking alignment state, and pushes the alignment coordinates to the display screen and the vehicle system. The vehicle body re-parks according to the alignment coordinates until the static alignment value meets the standard. The state update unit updates the real-time alignment state based on the offset distance, calculates the offset distance ds based on the center coordinates (x1, y1, z1) of the receiving coil and the center coordinates (x2, y2, z2) of the transmitting coil, and sets... The offset distance ds is obtained, and the offset distance ds is compared with the preset offset distance ds0. The state of the offset distance is judged according to the comparison result, and the real-time alignment state is updated according to the judgment result, wherein: When ds≥ds0, the state update unit determines the offset distance as a long distance and does not update the real-time alignment state. When ds < ds0, the state update unit determines that the offset distance is close, updates the real-time alignment state, and directly determines that the real-time alignment state is aligned.

5. The system of the new energy vehicle wireless charging efficiency optimization device according to claim 2, characterized in that, The metal monitoring charging module generates control data based on the target charging data and activates the charging mode based on the control data. The target charging data is input into the control data generation model to obtain the control data output by the control data generation model. The metal monitoring charging module activates the charging mode based on the control data. The metal monitoring and charging module monitors metal waste in real time and adjusts the charging mode based on the monitoring results. It compares the resonant frequency offset PM with a preset resonant frequency offset PM0, determines the state of the resonant frequency offset based on the comparison result, and outputs the real-time monitoring results based on the determination result. When PM≤PM0, the metal monitoring charging module determines that the resonant frequency offset is zero and outputs the absence of metal waste as the real-time monitoring result. When PM > PM0, the metal monitoring charging module determines that the resonant frequency offset is offset and outputs the presence of metal waste as a real-time monitoring result. When the metal monitoring charging module outputs the absence of metal waste as a real-time monitoring result, it does not adjust the charging mode. When the metal monitoring and charging module outputs the presence of metal waste as a real-time monitoring result, it adjusts the charging mode: turning off the charging mode and controlling the metal adsorption magnet until the real-time monitoring result shows that there is no metal waste.

6. The system of the new energy vehicle wireless charging efficiency optimization device according to claim 2, characterized in that, The charging mode optimization module includes: The temperature monitoring and optimization unit is used to update the charging mode based on the battery temperature in the target charging data, and also to optimize the mode update process based on weather attributes. The timeliness demand optimization unit is used to obtain the remaining charging time, correct the state update process based on the remaining charging time, and optimize the state correction process based on the time between the peak electricity price and the peak electricity price. The timeliness demand optimization unit is connected to the temperature monitoring optimization unit. The feature recognition optimization unit is used to optimize the process of pattern update and state correction based on the ID feature identification code. The feature recognition optimization unit is connected to the timeliness requirement optimization unit.

7. The system of the new energy vehicle wireless charging efficiency optimization device according to claim 6, characterized in that, The temperature monitoring and optimization unit updates the charging mode based on the battery temperature in the target charging data. It compares the battery temperature DW with a first preset battery temperature DW1 and a second preset battery temperature DW2, determines the battery temperature status based on the comparison result, and updates the charging mode accordingly. When DW≤DW1, the temperature monitoring and optimization unit determines that the battery temperature is low and updates the charging mode by adding a real-time preheating scheme to the charging mode. When DW1 < DW ≤ DW2, the temperature monitoring and optimization unit determines that the battery temperature is moderate and does not update the charging mode. When DW > DW2, the temperature monitoring and optimization unit determines that the battery temperature is high and updates the charging mode by turning off the charging mode. The temperature monitoring optimization unit optimizes the model update process based on weather attributes, compares the ambient temperature WH with the preset ambient temperature WH0, determines the attributes of the ambient temperature based on the comparison result, and outputs the weather attributes based on the determination result, wherein: When WH≥WH0, the temperature monitoring optimization unit determines that the ambient temperature is normal low temperature and outputs non-cold weather as the weather attribute. When WH < WH0, the temperature monitoring optimization unit determines that the ambient temperature is abnormally low and outputs cold weather as a weather attribute. The temperature monitoring optimization unit optimizes the mode update process when outputting cold weather as a weather attribute: when the battery temperature is low, the real-time preheating scheme is replaced with a preheating scheme, and the preheating scheme is added to the charging mode.

8. The system of the new energy vehicle wireless charging efficiency optimization device according to claim 7, characterized in that, The timeliness requirement optimization unit performs state correction during the state update process based on the remaining charging time. It calculates the remaining charging time tp based on the remaining required power kp and the charging rate vp, setting tp = kp / vp to obtain the remaining charging time tp. The remaining charging time tp is then compared with a preset remaining charging time tp0. Based on the comparison result, the state of the remaining charging time is determined, and the state update process is corrected based on the determination result. Wherein: When tp≥tp0, the timeliness requirement optimization unit determines the remaining charging time as a long time and does not perform state correction during the state update process. When tp < tp0, the timeliness requirement optimization unit determines that the remaining charging time is short, corrects the state update process, cancels the state update process, and expands the coil.

9. The system of the wireless charging efficiency optimization device for new energy vehicles according to claim 8, characterized in that, The timeliness demand optimization unit optimizes the state according to the process of state correction based on the time difference between the peak electricity price and the peak electricity price. It calculates the time difference between the peak electricity price and the peak electricity price based on the current time point td0 and the peak electricity price time point td2, and sets T2 = td2 - td0. The rechargeable amount dkp is calculated based on the peak electricity price distance time T2 and the charging rate vp, where dkp = T2 × vp. The rechargeable amount dkp is then compared with the remaining required electricity kp. Based on the comparison result, the status of the rechargeable amount is determined, and the status of the remaining charging time tp is optimized according to the determination result. Where: When dkp≥kp, the timeliness requirement optimization unit determines that the state of the rechargeable amount is coverable and does not optimize the state of the remaining charging time tp. When dkp < kp, the timeliness demand optimization unit determines that the rechargeable amount is not covered. It calculates the rechargeable amount difference ckm based on the rechargeable amount dkp and the remaining required amount kp, sets ckm = kp - dkp, obtains the rechargeable amount difference ckm, and pushes the rechargeable amount difference ckm to the vehicle system, so that the car owner can choose whether to continue charging after reaching the peak electricity price time. When a car owner chooses to continue charging after reaching the peak electricity price time, the remaining charging time tp status is not optimized. When a car owner chooses not to continue charging after reaching the peak electricity price time, the remaining charging time tp is optimized by replacing the remaining charging time tp with the distance time from the peak electricity price T2.

10. The system of the new energy vehicle wireless charging efficiency optimization device according to claim 9, characterized in that, The feature recognition optimization unit optimizes the pattern update and state correction process based on the ID feature recognition code. It uses a preset ID feature recognition code as an index and constructs a temperature and time-dependent usage database using the temperature usage habit range and time-dependent usage habit corresponding to the preset ID feature recognition code as association results. The unit then compares the ID feature recognition code with the preset ID feature recognition code and outputs the temperature usage habit range and time-dependent usage habit based on the comparison result. When the ID feature identification code matches the preset ID feature identification code, the temperature usage habit range and time usage habit corresponding to the preset ID feature identification code will be output from the temperature time-effect habit database; When the ID feature identification code is inconsistent with the preset ID feature identification code, the temperature usage range and time-of-use usage will not be output; When the ID feature identification code matches the preset ID feature identification code, the feature recognition optimization unit replaces the first preset ambient temperature WH1 and the second preset ambient temperature WH2 with the temperature usage habit range, and re-compares the ambient temperature WH with the first preset ambient temperature WH1 and the second preset ambient temperature WH2. Replace the preset remaining charging time tp0 with the usage habit based on timeliness, and re-compare the remaining charging time tp with the preset remaining charging time tp0.

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