Vehicle-mounted wireless charging control system and method based on CAN communication

Abstract

The present invention belongs to the field of wireless charging technology, and specifically relates to a vehicle-mounted wireless charging control system and method based on CAN communication. The present invention effectively solves the balance problem between charging efficiency and electromagnetic compatibility by real-time monitoring of environmental electromagnetic signals and dynamically adjusting charging frequency and other parameters. At the same time, the system periodically updates the device status and electromagnetic environment data during the charging process to ensure that the charging parameters are always in the optimal configuration. In addition, after charging is completed, the system will organize and store all relevant data to provide detailed data support for future charging optimization. These improvements not only improve charging efficiency, but also significantly enhance the system's anti-interference ability, thereby providing a safer and more efficient vehicle-mounted wireless charging experience.

Description

Technical Field

[0001] The present invention belongs to the technical field of wireless charging, and in particular relates to a vehicle-mounted wireless charging control system and method based on CAN communication. Background Art

[0002] Existing in-vehicle wireless charging systems usually rely on fixed charging parameters and frequency settings, which are preset at design time and remain unchanged throughout the charging process. Such systems communicate with various devices inside the vehicle via the CAN bus to obtain battery status information and control the charging process. However, this approach has some limitations: Limitations of fixed parameters: Since charging parameters are pre-set, they cannot be dynamically adjusted based on real-time environmental changes (such as electromagnetic interference) or changes in device status (such as battery health). This may lead to inefficient charging or electromagnetic compatibility issues.

[0003] Lack of dynamic monitoring and adjustment mechanism: Traditional in-vehicle wireless charging systems usually do not include dynamic monitoring functions for environmental electromagnetic signals. Therefore, when strong electromagnetic interference appears in the surrounding environment, the system cannot detect and take measures in time, which may cause charging interruption or device damage.

[0004] Insufficient data recording and optimization: Existing systems often do not have a complete mechanism to record and store key data from the charging process after charging is completed, making it difficult to provide a reference for subsequent optimization.

[0005] The main problem of the above-mentioned prior art is that it is unable to effectively solve the electromagnetic compatibility problem while ensuring charging efficiency. Since the charging parameters are fixed and there is no dynamic adjustment mechanism, the system is easily affected by external electromagnetic interference, resulting in reduced charging efficiency or even charging failure. Summary of the invention

[0006] The purpose of the present invention is to provide a vehicle-mounted wireless charging control system and method based on CAN communication, which not only improves the charging efficiency, but also significantly enhances the anti-interference ability of the system, thereby providing a safer and more efficient vehicle-mounted wireless charging experience to solve the problems in the prior art raised in the above background technology.

[0007] To achieve the above object, the present invention proposes a vehicle-mounted wireless charging control method based on CAN communication, comprising the following steps: At the beginning, the vehicle system scans and recognizes the identity of the access device through the CAN bus to establish a communication link; Based on the established communication link, the device battery status information is obtained and an adjustment instruction is sent to the central unit. After receiving the instruction, the central unit determines a preliminary charging strategy according to the battery status and selects an initial charging parameter set; The charging process is started using the selected parameter set, and dynamic monitoring of environmental electromagnetic signals is enabled. If abnormal electromagnetic interference is detected, the system will pause the current charging action, analyze the interference source, and adjust the frequency to avoid interference. The adjusted frequency is verified to see if it can effectively reduce interference without affecting charging efficiency. If successful, charging continues at the new frequency; During the charging process, the device status and electromagnetic environment data are updated periodically to ensure that the charging parameters are always in the optimal configuration; After charging is completed, all relevant data will be collated and stored for future optimization reference, and the charging circuit will be turned off and the system will be reset.

[0008] Preferably, the vehicle system scans and identifies the identity of the access device through the CAN bus to establish a communication link, including: The vehicle system sends a broadcast message to all nodes on the CAN bus to initiate an identification request; After receiving the broadcast message, the access device calculates its unique identity identifier and returns it to the vehicle system through a response message; The vehicle system receives the response message and verifies the validity of the unique identifier; The vehicle system establishes an encrypted communication link with the successfully authenticated device, and the encrypted link is achieved by generating a session key.

[0009] Preferably, acquiring the device battery status information based on the established communication link and sending an adjustment instruction to the central unit includes: The vehicle system sends a status query request to the device via an encrypted communication link; After receiving the query request, the device reads its battery voltage, current and temperature, and calculates the comprehensive health index; The device sends a response message containing the comprehensive health index and other battery status information back to the vehicle system; The vehicle system receives and parses the battery status information in the response message, generates adjustment instructions based on the comprehensive health index, and sends them to the central unit.

[0010] Preferably, after receiving the instruction, the central unit determines a preliminary charging strategy according to the battery status and selects an initial charging parameter set, including: The central unit parses the received adjustment instructions and extracts the comprehensive health index and other battery status information; According to the extracted comprehensive health index, a preliminary charging current intensity is calculated; Determine the optimal charging voltage by using the preliminary charging current intensity combined with the battery temperature; Based on the preliminary charging current intensity and the optimal charging voltage, an initial charging parameter set is generated.

[0011] Preferably, the method of starting the charging process using the selected parameter set and simultaneously starting the dynamic monitoring of the environmental electromagnetic signal includes: The central unit starts the charging circuit using the current intensity and voltage in the initial charging parameter set; After charging is started, the system begins to collect the electromagnetic signal strength of the surrounding environment in real time and records it as the initial background noise level; At fixed time intervals, the current electromagnetic signal strength is remeasured and the difference with the initial background noise level is calculated; If the difference exceeds a preset threshold, the charging parameters are adjusted to reduce electromagnetic interference.

[0012] Preferably, if abnormal electromagnetic interference is detected, the system will suspend the current charging action, analyze the interference source, and adjust the frequency to avoid interference, including: When the detected electromagnetic interference level exceeds the preset threshold, the system immediately suspends the charging operation; The system starts the interference source analysis module, collects electromagnetic signal spectrum data within a continuous period of time, and calculates the spectrum energy distribution; Based on the spectrum energy distribution, identify the main interference frequency range; The system reselects a new charging frequency to avoid interference based on the identified main interference frequency range.

[0013] Preferably, the adjusted frequency is verified to see whether it can effectively reduce interference without affecting charging efficiency. If successful, charging is continued at the new frequency, including: The system restarts charging at the new selected frequency and begins monitoring the water for new EMI; Compare the interference level at the new frequency with the original threshold to determine whether the interference has been effectively reduced; After confirming that the interference has been reduced, the system measures the charging efficiency at the new frequency; If the charging efficiency at the new frequency is not lower than the efficiency benchmark initially set, the frequency is confirmed as a valid frequency and continues to be used.

[0014] Preferably, during the charging process, the device status and electromagnetic environment data are periodically updated to ensure that the charging parameters are always in the optimal configuration, including: After charging begins, the system sets a fixed time interval; At each time interval, the system collects the current battery status information and electromagnetic interference level; Calculate a new comprehensive health index based on the collected battery status information and electromagnetic interference level; Based on the new comprehensive health index, the charging parameter set is dynamically adjusted to ensure that the charging process is always in the optimal configuration.

[0015] Preferably, after the charging is completed, all relevant data will be sorted and stored for future optimization reference, and the charging circuit will be turned off and the system will be reset, including: At the end of charging, the system records the current battery status information and EMI level; The system calculates the average efficiency over the entire charging process, based on previously periodically collected data points; The system generates a comprehensive performance report containing all key data and statistics; The system stores the comprehensive performance report in internal memory and executes the shutdown operation of the charging circuit and resets the system.

[0016] On the other hand, the present invention proposes a vehicle-mounted wireless charging control system based on CAN communication, comprising: The device identification and communication establishment module is used for the vehicle system to scan and identify the identity of the access device through the CAN bus at the beginning and establish a communication link; The battery status acquisition and preliminary strategy determination module is used to acquire the device battery status information based on the established communication link and send adjustment instructions to the central unit. After receiving the instructions, the central unit determines the preliminary charging strategy according to the battery status and selects the initial charging parameter set; The charging and dynamic monitoring module is used to start the charging process using the selected parameter set and to start the dynamic monitoring of the environmental electromagnetic signals. If abnormal electromagnetic interference is detected, the system will suspend the current charging action, analyze the interference source, and adjust the frequency to avoid interference. The frequency verification and continued charging module is used to verify whether the adjusted frequency can effectively reduce interference and does not affect charging efficiency. If successful, charging will continue at the new frequency. The periodic update and optimization module is used to periodically update the device status and electromagnetic environment data during the charging process to ensure that the charging parameters are always in the optimal configuration; Data storage and system reset: After charging is completed, all relevant data will be sorted and stored for future optimization reference. At the same time, the charging circuit will be turned off and the system will be reset.

[0017] Technical effects and advantages of the present invention: Compared with the prior art, the vehicle-mounted wireless charging control system and method based on CAN communication proposed by the present invention has the following advantages: The present invention effectively solves the balance problem between charging efficiency and electromagnetic compatibility by real-time monitoring of environmental electromagnetic signals and dynamically adjusting charging frequency and other parameters. At the same time, the system periodically updates the device status and electromagnetic environment data during the charging process to ensure that the charging parameters are always in the optimal configuration. In addition, after charging is completed, the system will organize and store all relevant data to provide detailed data support for future charging optimization. These improvements not only improve charging efficiency, but also significantly enhance the system's anti-interference ability, thereby providing a safer and more efficient in-vehicle wireless charging experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 This is a flow chart of the vehicle-mounted wireless charging control method based on CAN communication of the present invention; Figure 2 The block diagram of the vehicle-mounted wireless charging control system based on CAN communication of the present invention. DETAILED DESCRIPTION

[0019] The following will be combined with the accompanying drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments. The specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0020] The present invention provides Figure 1 The vehicle-mounted wireless charging control method based on CAN communication shown includes the following steps: At the beginning, the vehicle system scans and identifies the identity of the access device through the CAN bus to establish a communication link; specifically, it includes: The vehicle system sends a broadcast message to all nodes on the CAN bus to initiate an identification request. The request format is: Msg = [Header, ID_Request, Checksum], where Header is the fixed header information, ID_Request is the command byte for requesting identification, and Checksum is the checksum to ensure data integrity; By sending a broadcast message to all nodes on the CAN bus, the vehicle system can start the device identification process. This step ensures that the system can discover and connect to all potential charging devices.

[0021] After receiving the broadcast message, the access device calculates its unique identity identifier UID and returns it to the vehicle system through a response message. The response message format is: Resp_Msg=[Header,UID,Checksum], where: UID=(Device_Serial_Number*Prime_Number)modMax_Value, where Device_Serial_Number is the device serial number, Prime_Number is a fixed prime number, and Max_Value is the maximum value limit; after receiving the broadcast message, the device calculates its unique identity identifier (UID) and returns it to the vehicle system through a response message. This step ensures that each device has a unique identifier, which facilitates subsequent identity authentication and communication security.

[0022] The vehicle system receives the response message and verifies the validity of the UID. The verification formula is: Valid_UID=(Received_UID*Inverse_Prime_Number)modMax_Value. If Valid_UID is equal to Device_Serial_Number, the identity verification is successful. The vehicle system confirms the identity of the device by verifying the validity of the UID. This step ensures that only legitimate devices can establish a communication link with the system, enhancing the security of the system.

[0023] The vehicle system establishes an encrypted communication link with the successfully authenticated device. The encrypted link is achieved by generating a session key. The formula is: Session_Key = HMAC_SHA256(UID, Random_Seed), where HMAC_SHA256 represents a message authentication code using the SHA-256 hash algorithm, and Random_Seed is a random seed value generated from the vehicle system and the device. The vehicle system establishes an encrypted communication link with the successfully authenticated device to ensure the security of data transmission. This step prevents man-in-the-middle attacks and other potential security threats.

[0024] Embodiment 1

[0025] Assume there is an in-vehicle wireless charging system, which includes the following steps: Send a broadcast message: The vehicle system sends a broadcast message Msg = [Header, ID_Request, Checksum] to all nodes on the CAN bus. Assume that Header = 0x1234, ID_Request = 0x01, Checksum = 0xABCD.

[0026] The device responds and calculates the UID: After receiving the broadcast message, the access device calculates its UID: Assume that Device_Serial_Number = 123456789, Prime_Number = 65537, and Max_Value = 2^32.

[0027] The UID calculation result is: UID=(123456789*65537)mod4294967296=123456789.

[0028] The device sends a response message Resp_Msg = [Header, UID, Checksum], assuming that Checksum = 0xDCBA.

[0029] Verify the validity of the UID: After receiving the response message, the vehicle system calculates Valid_UID: Assume that Inverse_Prime_Number = 123456789 (this is the multiplicative inverse element of Prime_Number).

[0030] The verification formula is: Valid_UID=(123456789*123456789)mod4294967296=123456789.

[0031] Since Valid_UID is equal to Device_Serial_Number, authentication is successful.

[0032] Establish an encrypted communication link: The vehicle system and device each generate a random seed value, assuming that they are Random_Seed_Vehicle=123456 and Random_Seed_Device=654321 respectively.

[0033] Generate a session key using the UID and a random seed value: Session_Key=HMAC_SHA256(123456789,123456||654321), where || represents the concatenation operation.

[0034] Through the above steps, the vehicle system successfully identifies and verifies the identity of the access device and establishes a secure encrypted communication link, ensuring the security and reliability of data transmission. This process not only improves the safety of the system, but also provides a solid foundation for subsequent efficient charging.

[0035] Based on the established communication link, obtain the device battery status information and send adjustment instructions to the central unit; specifically include: The vehicle system sends a status query request to the device through an encrypted communication link. The request format is: Query_Msg = [Header, Query_Command, Checksum], where Header is the fixed header information, Query_Command is the command byte for querying the battery status, and Checksum is the checksum to ensure data integrity; the vehicle system sends a status query request to the device through an encrypted communication link to obtain the device's battery status information. This step ensures that the system can accurately understand the current battery status of the device and provide a basis for subsequent charging strategy adjustments.

[0036] After receiving the query request, the device reads parameters such as the battery voltage V_Batt, current I_Batt and temperature T_Batt, and calculates the comprehensive health index HCI. The formula for the comprehensive health index is: HCI=(V_Batt*I_Batt) / T_Batt, where V_Batt is the battery voltage, I_Batt is the battery current, and T_Batt is the battery temperature. This step provides a quantitative assessment of the device's battery health status, making it easier for the system to adjust the charging strategy based on the index.

[0037] The device sends a response message containing the comprehensive health index and other battery status information back to the vehicle system. The response message format is: Resp_Msg=[Header,HCI,Battery_Status,Checksum], where Battery_Status contains detailed battery status information; this step ensures that the vehicle system can obtain detailed battery status information for further processing and analysis.

[0038] The vehicle system receives and parses the battery status information in the response message, generates an adjustment command based on the comprehensive health index, and sends it to the central unit. The adjustment command formula is: Adjust_Cmd=Round(HCI*Adjustment_Factor), where Adjustment_Factor is a fixed adjustment factor used to convert the comprehensive health index to a specific adjustment command value, and Round means rounding to the nearest integer. This step enables the system to dynamically adjust the charging parameters according to the actual health status of the battery to optimize charging efficiency and safety.

[0039] Embodiment 2

[0040] Assume there is a car wireless charging system, including the following steps: Send a status query request: The vehicle system sends a status query request Query_Msg = [Header, Query_Command, Checksum] to the device through an encrypted communication link. Assume that Header = 0x5678, Query_Command = 0x02, Checksum = 0xEFCD.

[0041] The device reads the battery status and calculates the HCI: After receiving the query request, the device reads its battery voltage, current and temperature: Assume V_Batt=12.6V, I_Batt=2.5A, T_Batt=25°C.

[0042] Calculate the comprehensive health index: HCI=(12.6*2.5) / 25=1.26.

[0043] The device sends a response message: The device sends a response message containing the comprehensive health index and other battery status information back to the vehicle system: Assume that Resp_Msg = [Header, HCI, Battery_Status, Checksum], where Header = 0x5678, HCI = 1.26, Battery_Status = [12.6, 2.5, 25], and Checksum = 0xDCBA.

[0044] Generate adjustment instructions: The vehicle system receives and parses the battery status information in the response message and generates adjustment instructions based on the comprehensive health index: Assume Adjustment_Factor=10.

[0045] Calculate the adjustment command: Adjust_Cmd=Round(1.26*10)=13.

[0046] Through the above steps, the vehicle system successfully obtains the battery status information of the device and generates corresponding adjustment instructions based on the comprehensive health index. The specific implementation process is as follows: The vehicle system sends a query request Query_Msg=[0x5678,0x02,0xEFCD].

[0047] The device calculates the comprehensive health index HCI = 1.26 and generates a response message Resp_Msg = [0x5678, 1.26, [12.6, 2.5, 25], 0xDCBA].

[0048] The vehicle system receives the response message, calculates the adjustment command Adjust_Cmd=13 and sends it to the central unit.

[0049] This process not only ensures that the vehicle system can accurately understand the battery status of the device, but also dynamically adjusts the charging strategy according to the battery health status, improving charging efficiency and safety.

[0050] After receiving the command, the central unit determines the initial charging strategy based on the battery status and selects the initial charging parameter set; specifically, it includes: The central unit parses the received adjustment instructions, extracts the comprehensive health index HCI and other battery status information, and the extraction formula is: Extracted_HCI=Resp_Msg[HCI], Resp_Msg[HCI] represents the comprehensive health index extracted from the response message; this step ensures that the system can accurately obtain the current battery health status of the device and provide basic data for subsequent charging strategy formulation.

[0051] Based on the extracted comprehensive health index HCI, a preliminary charging current intensity I_Init is calculated. The preliminary charging current intensity formula is: I_Init=HCI*Ref_Current, where Ref_Current is a reference current value based on the device type; this step determines the appropriate charging current based on the current health status of the device to ensure the safety and efficiency of the charging process.

[0052] The optimal charging voltage V_Opt is determined by using the initial charging current intensity I_Init and the battery temperature T_Batt. The optimal charging voltage formula is: V_Opt=I_Init*(1+T_Batt / Temp_Coeff), where Temp_Coeff is a temperature coefficient used to compensate for the impact of temperature changes on the charging voltage. This step takes into account the impact of battery temperature on the charging voltage to ensure that the charging voltage can remain in the optimal state under different temperature conditions.

[0053] Based on the initial charging current intensity I_Init and the optimal charging voltage V_Opt, the initial charging parameter set Param_Set is generated. The formula of the initial charging parameter set is: Param_Set=[I_Init,V_Opt,Total_Charge_Time], where Total_Charge_Time is the charging time estimated based on the device capacity and the initial charging current intensity. This step brings together all the necessary charging parameters to facilitate the system to perform specific charging operations and estimate the charging time.

[0054] Embodiment 3

[0055] Assume there is an in-vehicle wireless charging system, which includes the following steps: Parse the received adjustment instructions and extract the comprehensive health index: The central unit parses the received adjustment instructions and extracts the comprehensive health index HCI: Assume Resp_Msg[HCI]=1.26.

[0056] Calculate the initial charging current intensity: According to the extracted comprehensive health index (HCI), calculate the initial charging current intensity (I_Init): Assume Ref_Current = 5A (reference current value set based on device type).

[0057] Calculation formula: I_Init=1.26*5=6.3A.

[0058] Determine the optimal charging voltage: Using the initial charging current intensity (I_Init) combined with the battery temperature (T_Batt), determine the optimal charging voltage (V_Opt): Assume T_Batt=25°C, Temp_Coeff=100.

[0059] Calculation formula: V_Opt=6.3*(1+25 / 100)=6.3*1.25=7.875V.

[0060] Generate an initial charging parameter set: Based on the preliminary charging current intensity (I_Init) and the optimal charging voltage (V_Opt), generate the initial charging parameter set (Param_Set): Assuming the device capacity is 10Ah, the estimated charging time is Total_Charge_Time = device capacity / charging current = 10 / 6.3 ≈ 1.59 hours.

[0061] The final generated initial charging parameter set is: Param_Set=[6.3A, 7.875V, 1.59 hours].

[0062] Through the above steps, the central unit successfully determines the preliminary charging strategy according to the battery status of the device and generates the initial charging parameter set. This process not only improves the charging efficiency, but also ensures the safety and reliability of the charging process.

[0063] The charging process is started using the selected parameter set, and dynamic monitoring of the environmental electromagnetic signals is started at the same time; specifically, it includes: The central unit uses the current intensity I_Init and voltage V_Opt in the initial charging parameter set Param_Set to start the charging circuit. The starting formula is: Charge_Start=(I_Init*V_Opt) / Eff_Factor, where Eff_Factor is an efficiency factor used to compensate for energy transmission losses; this step ensures that the system can start the charging process according to the specific needs of the device and compensate for energy transmission losses.

[0064] After charging is started, the system begins to collect the electromagnetic signal strength of the surrounding environment in real time and records it as the initial background noise level Noise_Level_0. The formula for the initial background noise level is: Noise_Level_0=Sum(Env_Signal[i]) / Sample_Count, where Env_Signal[i] is the electromagnetic signal strength value of the i-th sample, and Sample_Count is the total number of samples. This step provides a baseline noise level for the charging environment, which is convenient for subsequent monitoring and comparison.

[0065] At fixed time intervals t_interval, the current electromagnetic signal strength is remeasured and the difference Curr_Noise_Diff with the initial background noise level is calculated. The difference calculation formula is: Curr_Noise_Diff=Abs(Current_Noise_Level-Noise_Level_0), where Current_Noise_Level is the average value of the currently measured electromagnetic signal strength. This step dynamically monitors changes in environmental electromagnetic interference and detects abnormal conditions in a timely manner.

[0066] If Curr_Noise_Diff exceeds the preset threshold Max_Noise_Level, the charging parameters are adjusted to reduce electromagnetic interference. The adjustment formula is: Adjusted_Param_Set=[I_Init*(1-Curr_Noise_Diff / Max_Noise_Level),V_Opt*(1-Curr_Noise_Diff / Max_Noise_Level)], which reduces electromagnetic interference by reducing current and voltage. This step reduces electromagnetic interference by reducing current and voltage to ensure the safety and stability of the charging process.

[0067] Embodiment 4

[0068] Assume there is an in-vehicle wireless charging system, which includes the following steps: Start charging circuit: The central unit starts the charging circuit with the current intensity and voltage set in the initial charging parameters: Assume I_Init=6.3A, V_Opt=7.875V, Eff_Factor=0.9.

[0069] Calculation formula: Charge_Start=(6.3*7.875) / 0.9≈55.125W.

[0070] Record the initial background noise level: After charging is started, the system begins to collect the electromagnetic signal strength of the surrounding environment in real time and records it as the initial background noise level: Assume that the total number of samples Sample_Count = 10, and the sampling values ​​​​are [0.1, 0.2, 0.15, 0.12, 0.13, 0.14, 0.11, 0.16, 0.17, 0.18] respectively.

[0071] Calculation formula: Noise_Level_0=(0.1+0.2+0.15+0.12+0.13+0.14+0.11+0.16+0.17+0.18) / 10=0.145.

[0072] Remeasure the current electromagnetic signal strength and calculate the difference: Every fixed time interval t_interval, re-measure the current electromagnetic signal strength and calculate the difference with the initial background noise level: Assume that the average value of the electromagnetic signal strength currently measured is Current_Noise_Level=0.25.

[0073] Calculation formula: Curr_Noise_Diff=Abs(0.25-0.145)=0.105.

[0074] Adjust charging parameters to reduce electromagnetic interference: If Curr_Noise_Diff exceeds the preset threshold Max_Noise_Level=0.1, the charging parameters are adjusted: Calculation formula: Adjusted_Param_Set=[6.3*(1-0.105 / 0.1),7.875*(1-0.105 / 0.1)]=[6.3*0.9,7.875*0.9]=[5.67A,7.0875V].

[0075] Through the above steps, the system successfully started the charging process and started dynamic monitoring of environmental electromagnetic signals. When the electromagnetic interference detected exceeds the preset threshold, the system automatically adjusts the charging parameters to ensure the safety and stability of the charging process. This process not only improves the charging efficiency, but also enhances the system's anti-interference ability.

[0076] If abnormal electromagnetic interference is detected, the system will suspend the current charging action, analyze the interference source, and adjust the frequency to avoid interference; specifically: When the detected electromagnetic interference level Curr_Noise_Diff exceeds the preset threshold Max_Noise_Level, the system immediately suspends the charging operation. The suspension condition is: IfCurr_Noise_Diff>Max_Noise_LevelThenPause_Charging=True; this step ensures the safety of the charging process in a high-interference environment and avoids equipment damage or reduced charging efficiency.

[0077] The system starts the interference source analysis module, collects electromagnetic signal spectrum data in a continuous time period, and calculates the spectrum energy distribution Spectrum_Energy. The spectrum energy distribution formula is: Spectrum_Energy=Sum(Signal_Freq[i]^2) / Sample_Count, where Signal_Freq[i] is the signal strength at the i-th frequency point, and Sample_Count is the total number of samples. This step provides detailed electromagnetic environment information, which facilitates the identification of the main interference frequency range.

[0078] Based on the spectrum energy distribution Spectrum_Energy, the main interference frequency range Interference_Band is identified. The interference frequency range formula is: Interference_Band=[Freq_Start,Freq_End], where Freq_Start and Freq_End are the starting and ending frequencies higher than the average energy level in the spectrum energy distribution. This step helps the system determine the specific interference frequency range so that targeted measures can be taken to avoid interference.

[0079] The system reselects a new charging frequency New_Frequency based on the identified main interference frequency range Interference_Band to avoid interference. The new frequency selection formula is: New_Frequency=(Freq_End+Next_Freq_Start) / 2, where Next_Freq_Start is the first available frequency point immediately after Interference_Band. This step ensures that the charging process can continue in a low-interference environment by adjusting the charging frequency.

[0080] Embodiment 5

[0081] Assume there is an in-vehicle wireless charging system, which includes the following steps: Pause charging operation: When the detected electromagnetic interference level exceeds the preset threshold, the system immediately suspends charging operation: Assume Curr_Noise_Diff=0.15, Max_Noise_Level=0.1.

[0082] Judgment condition: If0.15>0.1ThenPause_Charging=True, if the condition is met, the system will pause charging.

[0083] Start the interference source analysis module and calculate the spectrum energy distribution: The system starts the interference source analysis module, collects electromagnetic signal spectrum data within a continuous period of time, and calculates the spectrum energy distribution: Assume that the total number of samples Sample_Count = 10, and the signal strength at each frequency point is [0.2, 0.3, 0.1, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0] respectively.

[0084] Calculation formula: Spectrum_Energy=(0.2^2+0.3^2+0.1^2+0.4^2+0.5^2+0.6^2+0.7^2+0.8^2+0.9^2+1.0^2) / 10≈0.425.

[0085] Identify the main interfering frequency ranges: Based on the spectrum energy distribution, the main interference frequency range is identified: Assume the average energy level is 0.425 and the frequency points above this level are [0.5, 0.6, 0.7, 0.8, 0.9, 1.0].

[0086] The identified interference frequency range is: Interference_Band=[0.5,1.0].

[0087] Reselect a new charging frequency: Reselect a new charging frequency based on the identified main interference frequency range: Assume that the first available frequency point Next_Freq_Start=1.1 immediately after the interference frequency range.

[0088] Calculation formula: New_Frequency=(1.0+1.1) / 2=1.05.

[0089] The specific implementation process is as follows: Pause charging operation: Pause condition: If0.15>0.1ThenPause_Charging=True, the system pauses charging.

[0090] Start the interference source analysis module and calculate the spectral energy distribution: Spectral energy distribution formula: Spectrum_Energy=(0.2^2+0.3^2+0.1^2+0.4^2+0.5^2+0.6^2+0.7^2+0.8^2+0.9^2+1.0^2) / 10≈0.425。

[0091] Identify the main interference frequency range: Interference frequency range formula: Interference_Band=[0.5,1.0]。

[0092] Re-select a new charging frequency: New frequency selection formula: New_Frequency=(1.0+1.1) / 2=1.05。

[0093] Through the above steps, the system successfully pauses the charging operation when detecting abnormal electromagnetic interference, and selects a new charging frequency by analyzing the interference source, ensuring that the charging process can continue in a low-interference environment. This process not only improves the charging efficiency, but also enhances the anti-interference ability of the system, ensuring the safety and stability of the charging process.

[0094] Verify whether the adjusted frequency can effectively reduce interference and does not affect the charging efficiency. If successful, continue charging at the new frequency; specifically including: The system restarts charging at the selected new frequency New_Frequency and starts monitoring the new electromagnetic interference level Curr_Noise_Diff_New. The monitoring formula is: Curr_Noise_Diff_New=Abs(Current_Noise_Level_New-Noise_Level_0), where Current_Noise_Level_New is the average value of the electromagnetic signal intensity at the new frequency; this step ensures that the system can continue charging at the new frequency while monitoring the electromagnetic interference situation in real time.

[0095] Compare the interference level Curr_Noise_Diff_New at the new frequency with the original threshold Max_Noise_Level to determine whether the interference has been effectively reduced. The judgment formula is: IfCurr_Noise_Diff_New<Max_Noise_LevelThenReduced_Interference=True; this step verifies whether the new frequency can significantly reduce electromagnetic interference.

[0096] After confirming that the interference has been reduced, the system measures the charging efficiency Charge_Efficiency at the new frequency. The charging efficiency calculation formula is: Charge_Efficiency=(Charge_Energy / Time_Elapsed) / (I_Init*V_Opt), where Charge_Energy is the energy transmitted per unit time at the new frequency, and Time_Elapsed is the elapsed time; this step evaluates the impact of the new frequency on the charging efficiency, ensuring that the charging process not only reduces interference but also maintains efficient energy transmission.

[0097] If the charging efficiency Charge_Efficiency at the new frequency is not lower than the efficiency benchmark Ref_Efficiency set initially, the frequency is confirmed as a valid frequency and continues to be used. Confirm the formula: IfCharge_Efficiency>=Ref_EfficiencyThenContinue_Charging=True, the system keeps charging at the new frequency. This step ensures that the system can continue charging with low interference and high efficiency.

[0098] Embodiment 6

[0099] Assume there is a car wireless charging system, including the following steps: Restart charging and monitor the new EMI level: The system restarts charging at the selected new frequency (New_Frequency) and begins monitoring the new EMI level: Assume New_Frequency=1.05MHz.

[0100] Assume that the current average electromagnetic signal strength at the new frequency Current_Noise_Level_New=0.12, and the initial background noise level Noise_Level_0=0.145.

[0101] Calculation formula: Curr_Noise_Diff_New=Abs(0.12-0.145)=0.025.

[0102] Determine whether interference is effectively reduced: Compare the interference level at the new frequency with the original threshold to determine whether the interference has been effectively reduced: Assume Max_Noise_Level=0.1.

[0103] Judgment condition: If0.025<0.1ThenReduced_Interference=True, the condition is met and it is confirmed that the interference is reduced.

[0104] Measuring charging efficiency at the new frequency: After confirming that the interference has been reduced, the system measures the charging efficiency at the new frequency: Assume Charge_Energy=5W, Time_Elapsed=1h, I_Init=6.3A, V_Opt=7.875V.

[0105] Calculation formula: Charge_Efficiency=(5 / 1) / (6.3*7.875)≈0.101.

[0106] Confirm the validity of the new frequency and proceed with use: If the charging efficiency at the new frequency is not lower than the efficiency benchmark initially set, confirm that the frequency is a valid frequency and continue to use it: Assume Ref_Efficiency=0.1.

[0107] Judgment condition: If0.101>=0.1ThenContinue_Charging=True, if the condition is met, the system continues to charge at the new frequency.

[0108] Through the above steps, the system successfully restarted charging at the new frequency and verified that the new frequency can effectively reduce electromagnetic interference without affecting charging efficiency. This process not only improves the safety and stability of the charging process, but also ensures the efficient operation of the system.

[0109] During the charging process, the device status and electromagnetic environment data are updated periodically to ensure that the charging parameters are always in the optimal configuration; specifically, the following are included: After charging starts, the system sets a fixed time interval t_interval to periodically collect device status and electromagnetic environment data. The time interval formula is: t_interval=Total_Charge_Time / N_Samples, where Total_Charge_Time is the total charging time and N_Samples is the predetermined number of samples. This step ensures that the system can regularly obtain the latest battery status information and electromagnetic interference level in order to dynamically adjust the charging parameters.

[0110] At each t_interval, the system collects the current battery status information and the electromagnetic interference level Curr_Noise_Diff_Current; The acquisition formula is: Battery_Status_Current=[V_Current,I_Current] and Curr_Noise_Diff_Current=Abs(Current_Noise_Level-Noise_Level_0); this step provides real-time battery health status and electromagnetic interference conditions, providing a basis for subsequent optimization.

[0111] Based on the collected battery status information and electromagnetic interference level, a new comprehensive health index HCI_New is calculated. The comprehensive health index formula is: HCI_New=(V_Current*I_Current) / Curr_Noise_Diff_Current, using the current voltage, current and electromagnetic interference level; this step provides a quantitative assessment of the current health of the battery, making it easier for the system to adjust the charging strategy based on the index.

[0112] According to the new comprehensive health index HCI_New, the charging parameter set Param_Set_New is dynamically adjusted to ensure that the charging process is always in the optimal configuration. The adjustment formula is: Param_Set_New=[I_Init*HCI_New / Init_HCI, V_Opt*HCI_New / Init_HCI, Total_Charge_Time], where Init_HCI is the initial set comprehensive health index benchmark value. This step enables the system to adjust the charging parameters in real time according to the actual health status of the battery and the electromagnetic interference situation, and optimize the charging efficiency and safety.

[0113] Embodiment 7

[0114] Assume there is a car wireless charging system, including the following steps: To set a fixed time interval: After charging begins, the system sets a fixed time interval to periodically collect device status and electromagnetic environment data: Assume Total_Charge_Time=1.59h, N_Samples=10.

[0115] Calculation formula: t_interval=1.59 / 10≈0.159h (approximately 9.54 minutes).

[0116] Collect current battery status information and electromagnetic interference level: At each t_interval, the system collects the current battery status information and electromagnetic interference level: Assume that the current battery voltage V_Current=12.6V, the battery current I_Current=6.3A, the current noise level Current_Noise_Level=0.12, and the initial background noise level Noise_Level_0=0.145.

[0117] Collection formula: Battery_Status_Current=[12.6,6.3].

[0118] Calculation formula: Curr_Noise_Diff_Current=Abs(0.12-0.145)=0.025.

[0119] Calculate the new comprehensive health index: Based on the collected battery status information and electromagnetic interference level, a new comprehensive health index is calculated: Calculation formula: HCI_New=(12.6*6.3) / 0.025≈3175.2.

[0120] Dynamically adjust charging parameter set: Dynamically adjust the charging parameter set based on the new comprehensive health index: Assuming that the initial set comprehensive health index benchmark value Init_HCI=1.26, the preliminary calculated charging current intensity I_Init=6.3A, and the optimal charging voltage V_Opt=7.875V.

[0121] Adjustment formula: Param_Set_New=[6.3*3175.2 / 1.26,7.875*3175.2 / 1.26,1.59]≈[15876A,19845V,1.59h].

[0122] In actual applications, the current and voltage values ​​in the calculation results are abnormally high (such as [15876A, 19845V]), which is obviously inconsistent with the actual situation. Therefore, it is recommended to appropriately adjust the use of the comprehensive health index (HCI_New) or introduce other restrictions, such as the maximum allowable current and voltage values, in actual operation to ensure that the adjusted parameters are within a reasonable range.

[0123] After charging is completed, all relevant data will be collated and stored for future optimization reference, and the charging circuit will be turned off and the system will be reset; specifically: At the end of charging, the system records the current battery status information and electromagnetic interference level Curr_Noise_Diff_Final. The recording formula is: Final_Status=[V_Final,I_Final,Curr_Noise_Diff_Final]; This step ensures that the system can save key data at the end of charging, providing a basis for subsequent analysis and optimization.

[0124] The system calculates the average efficiency Avg_Efficiency during the entire charging process based on the data points collected periodically before. The average efficiency formula is: Avg_Efficiency=Sum(Charge_Efficiency[i]) / N_Samples, where Charge_Efficiency[i] is the charging efficiency at each sampling point and N_Samples is the total number of samples. This step provides an overall evaluation of the entire charging process, which facilitates the subsequent optimization of the charging strategy.

[0125] The system generates a comprehensive performance report Performance_Report, which contains all key data and statistical information. The formula of the comprehensive performance report is: Performance_Report=[Final_Status,Avg_Efficiency,Param_Set_History], where Param_Set_History is the historical record of all adjusted charging parameter sets during the entire charging process; this step summarizes all important data in the charging process for subsequent analysis and optimization.

[0126] The system stores the comprehensive performance report in the internal memory, and performs the closing operation of the charging circuit and the reset of the system. The storage operation formula is: Store(Performance_Report), followed by the closing operation of the charging circuit: Close_Charging_Circuit=True, and then resets the system: Reset_System=True. This step ensures the safe storage of data and restores the system to its initial state, ready for the next charging operation.

[0127] Embodiment 8

[0128] Assume there is an in-vehicle wireless charging system, which includes the following steps: Record battery status information and EMI level at the end of charging: At the end of charging, the system records the current battery status information and EMI level: Assume that the battery voltage V_Final = 13.0V, the battery current I_Final = 0.5A, and the electromagnetic interference level Curr_Noise_Diff_Final = 0.02 at the end of charging.

[0129] Record the formula: Final_Status=[13.0,0.5,0.02].

[0130] Calculate the average efficiency during the entire charging process: The system calculates the average efficiency over the entire charging process: Assume that the charging efficiency of each sampling point is [0.98, 0.96, 0.97, 0.95, 0.98, 0.96, 0.97, 0.95, 0.98, 0.96], and the total number of sampling times N_Samples = 10.

[0131] Calculation formula: Avg_Efficiency=(0.98+0.96+0.97+0.95+0.98+0.96+0.97+0.95+0.98+0.96) / 10≈0.965.

[0132] Generate comprehensive performance reports: The system generates a comprehensive performance report containing all key data and statistics: Assume that during the entire charging process, the adjusted charging parameter set history is Param_Set_History=[[6.3,7.875],[5.67,7.0875],[6.0,7.5]].

[0133] Comprehensive performance report formula: Performance_Report=[[13.0,0.5,0.02],0.965,[[6.3,7.875],[5.67,7.0875],[6.0,7.5]]].

[0134] Stores a comprehensive performance report and turns off the charging circuit and resets the system: The system stores the comprehensive performance report in the internal memory and performs the shutdown operation of the charging circuit and resets the system: Store operation: Store(Performance_Report).

[0135] Close charging circuit operation: Close_Charging_Circuit=True.

[0136] Reset system: Reset_System=True.

[0137] Through the above steps, the system successfully recorded the key data at the end of charging, calculated the average efficiency of the entire charging process, and generated a detailed performance report. These measures not only improved the reliability and safety of the system, but also provided valuable data support for future optimization.

[0138] On the other hand, the present invention proposes a vehicle-mounted wireless charging control system based on CAN communication, such as Figure 2 As shown, including: The device identification and communication establishment module is used for the vehicle system to scan and identify the identity of the access device through the CAN bus at the beginning and establish a communication link; The battery status acquisition and preliminary strategy determination module is used to acquire the device battery status information based on the established communication link and send adjustment instructions to the central unit. After receiving the instructions, the central unit determines the preliminary charging strategy according to the battery status and selects the initial charging parameter set; The charging and dynamic monitoring module is used to start the charging process using the selected parameter set and to start the dynamic monitoring of the environmental electromagnetic signals. If abnormal electromagnetic interference is detected, the system will suspend the current charging action, analyze the interference source, and adjust the frequency to avoid interference. The frequency verification and continued charging module is used to verify whether the adjusted frequency can effectively reduce interference and does not affect charging efficiency. If successful, charging will continue at the new frequency. The periodic update and optimization module is used to periodically update the device status and electromagnetic environment data during the charging process to ensure that the charging parameters are always in the optimal configuration; Data storage and system reset: After charging is completed, all relevant data will be sorted and stored for future optimization reference. At the same time, the charging circuit will be turned off and the system will be reset.

[0139] In addition, the above modules are also used to implement other steps of the above-mentioned vehicle-mounted wireless charging control method based on CAN communication when executed, which will not be described one by one here.

[0140] In summary, the present invention effectively solves the balance problem between charging efficiency and electromagnetic compatibility by real-time monitoring of environmental electromagnetic signals and dynamically adjusting charging frequency and other parameters. At the same time, the system periodically updates the device status and electromagnetic environment data during the charging process to ensure that the charging parameters are always in the optimal configuration. In addition, after charging is completed, the system will organize and store all relevant data to provide detailed data support for future charging optimization. These improvements not only improve charging efficiency, but also significantly enhance the system's anti-interference ability, thereby providing a safer and more efficient in-vehicle wireless charging experience.

[0141] Finally, it should be noted that the above is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, it is still possible for those skilled in the art to modify the technical solutions described in the aforementioned embodiments or to make equivalent substitutions for some of the technical features therein. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A vehicle-mounted wireless charging control method based on CAN communication, characterized in that: The following steps are involved: At the beginning, the vehicle system scans and recognizes the identity of the access device through the CAN bus to establish a communication link; Based on the established communication link, the device battery status information is obtained and an adjustment instruction is sent to the central unit. After receiving the instruction, the central unit determines a preliminary charging strategy according to the battery status and selects an initial charging parameter set; The charging process is started using the selected parameter set, and dynamic monitoring of environmental electromagnetic signals is enabled. If abnormal electromagnetic interference is detected, the system will pause the current charging action, analyze the interference source, and adjust the frequency to avoid interference. The adjusted frequency is verified to see if it can effectively reduce interference without affecting charging efficiency. If successful, charging continues at the new frequency; During the charging process, the device status and electromagnetic environment data are updated periodically to ensure that the charging parameters are always in the optimal configuration; After charging is completed, all relevant data will be collated and stored for future optimization reference, and the charging circuit will be turned off and the system will be reset.

2. The vehicle-mounted wireless charging control method based on CAN communication according to claim 1 is characterized in that: The vehicle system scans and identifies the identity of the access device through the CAN bus to establish a communication link, including: The vehicle system sends a broadcast message to all nodes on the CAN bus to initiate an identification request; After receiving the broadcast message, the access device calculates its unique identity identifier and returns it to the vehicle system through a response message; The vehicle system receives the response message and verifies the validity of the unique identifier; The vehicle system establishes an encrypted communication link with the successfully authenticated device, and the encrypted link is achieved by generating a session key.

3. The vehicle-mounted wireless charging control method based on CAN communication according to claim 2 is characterized in that: The acquiring of device battery status information based on the established communication link and sending an adjustment instruction to the central unit includes: The vehicle system sends a status query request to the device via an encrypted communication link; After receiving the query request, the device reads its battery voltage, current and temperature, and calculates the comprehensive health index; The device sends a response message containing the comprehensive health index and other battery status information back to the vehicle system; The vehicle system receives and parses the battery status information in the response message, generates adjustment instructions based on the comprehensive health index, and sends them to the central unit.

4. The vehicle-mounted wireless charging control method based on CAN communication according to claim 3 is characterized in that: After receiving the instruction, the central unit determines a preliminary charging strategy according to the battery status and selects an initial charging parameter set, including: The central unit parses the received adjustment instructions and extracts the comprehensive health index and battery status information; According to the extracted comprehensive health index, a preliminary charging current intensity is calculated; Determine the optimal charging voltage by using the preliminary charging current intensity combined with the battery temperature; Based on the preliminary charging current intensity and the optimal charging voltage, an initial charging parameter set is generated.

5. The vehicle-mounted wireless charging control method based on CAN communication according to claim 4 is characterized in that: The method of starting the charging process using the selected parameter set and simultaneously starting the dynamic monitoring of the environmental electromagnetic signal includes: The central unit starts the charging circuit using the current intensity and voltage in the initial charging parameter set; After charging is started, the system begins to collect the electromagnetic signal strength of the surrounding environment in real time and records it as the initial background noise level; At fixed time intervals, the current electromagnetic signal strength is remeasured and the difference with the initial background noise level is calculated; If the difference exceeds a preset threshold, the charging parameters are adjusted to reduce electromagnetic interference.

6. The vehicle-mounted wireless charging control method based on CAN communication according to claim 5 is characterized in that: If abnormal electromagnetic interference is detected, the system will suspend the current charging action, analyze the interference source, and adjust the frequency to avoid interference, including: When the detected electromagnetic interference level exceeds the preset threshold, the system immediately suspends the charging operation; The system starts the interference source analysis module, collects electromagnetic signal spectrum data within a continuous period of time, and calculates the spectrum energy distribution; Based on the spectrum energy distribution, identify the main interference frequency range; The system reselects a new charging frequency to avoid interference based on the identified main interference frequency range.

7. The vehicle-mounted wireless charging control method based on CAN communication according to claim 6 is characterized in that: The adjusted frequency is verified to see whether it can effectively reduce interference without affecting charging efficiency. If successful, charging continues at the new frequency, including: The system restarts charging at the new selected frequency and begins monitoring the water for new EMI; Compare the interference level at the new frequency with the original threshold to determine whether the interference has been effectively reduced; After confirming that the interference has been reduced, the system measures the charging efficiency at the new frequency; If the charging efficiency at the new frequency is not lower than the efficiency benchmark initially set, the frequency is confirmed as a valid frequency and continues to be used.

8. The vehicle-mounted wireless charging control method based on CAN communication according to claim 7 is characterized in that: During the charging process, the device status and electromagnetic environment data are periodically updated to ensure that the charging parameters are always in the optimal configuration, including: After charging begins, the system sets a fixed time interval; At each time interval, the system collects the current battery status information and electromagnetic interference level; Calculate a new comprehensive health index based on the collected battery status information and electromagnetic interference level; Based on the new comprehensive health index, the charging parameter set is dynamically adjusted to ensure that the charging process is always in the optimal configuration.

9. The vehicle-mounted wireless charging control method based on CAN communication according to claim 8, characterized in that: After the charging is completed, all relevant data will be collated and stored for future optimization reference, and the charging circuit will be turned off and the system will be reset, including: At the end of charging, the system records the current battery status information and EMI level; The system calculates the average efficiency over the entire charging process, based on previously periodically collected data points; The system generates a comprehensive performance report containing all key data and statistics; The system stores the comprehensive performance report in internal memory and executes the shutdown operation of the charging circuit and resets the system.

10. A vehicle-mounted wireless charging control system based on CAN communication for implementing the method as claimed in any one of claims 1 to 9, characterized in that: include: The device identification and communication establishment module is used for the vehicle system to scan and identify the identity of the access device through the CAN bus at the beginning and establish a communication link; The battery status acquisition and preliminary strategy determination module is used to acquire the device battery status information based on the established communication link and send adjustment instructions to the central unit. After receiving the instructions, the central unit determines the preliminary charging strategy according to the battery status and selects the initial charging parameter set; The charging and dynamic monitoring module is used to start the charging process using the selected parameter set and to start the dynamic monitoring of the environmental electromagnetic signals. If abnormal electromagnetic interference is detected, the system will suspend the current charging action, analyze the interference source, and adjust the frequency to avoid interference. The frequency verification and continued charging module is used to verify whether the adjusted frequency can effectively reduce interference and does not affect charging efficiency. If successful, charging will continue at the new frequency. The periodic update and optimization module is used to periodically update the device status and electromagnetic environment data during the charging process to ensure that the charging parameters are always in the optimal configuration; Data storage and system reset: After charging is completed, all relevant data will be sorted and stored for future optimization reference. At the same time, the charging circuit will be turned off and the system will be reset.

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