Control Method for Wireless Charging System of Electric Vehicles Based on Adaptive Voltage Filter

Abstract

This invention discloses a control method for a wireless charging system for electric vehicles based on an adaptive voltage filter. By introducing an adaptive filter, this invention achieves precise filtering and control of the system voltage without the need for additional sensors. Furthermore, by introducing online input gain identification and an adaptive filter module, this invention achieves dynamic output voltage regulation of the wireless charging system using only data from a single sensor. Therefore, the method proposed in this invention significantly improves voltage accuracy and tuning performance, reduces initial implementation costs and subsequent maintenance costs, and greatly enhances the stability of the control system.

Description

Technical Field

[0001] This invention relates to a voltage control method for a dynamic wireless charging system for electric vehicles in the field of wireless power transmission for electric vehicles, and particularly to a voltage control method and system for a dynamic wireless charging system for electric vehicles based on an adaptive filter. Background Technology

[0002] Electric vehicles (EVs), as a core component of future transportation, demonstrate strong competitiveness and drive the transformation and upgrading of the automotive industry due to their significant advantages in zero emissions, no dependence on fossil fuels, efficient energy utilization, convenient maintenance, and quiet driving. However, EVs still face the significant challenge of limited driving range during long-distance travel. Traditional battery charging methods have several drawbacks, such as high infrastructure construction costs, limited charging station coverage, long charging times, and safety hazards during charging. These issues restrict the widespread application of EVs, especially in long-distance travel or long-distance driving scenarios. With continuous technological advancements, wireless charging technology has developed rapidly and emerged as a potential solution to these problems. In particular, dynamic wireless charging technology, which can continuously provide power to EVs while the vehicle is in motion, has attracted widespread attention. This technology transmits power to the vehicle through sensors and energy transmitters laid on the road, eliminating the need to stop or plug in charging equipment, greatly improving the convenience of using EVs and expanding the diversity of travel options. Therefore, dynamic wireless charging technology is considered an important direction for the future development of EVs, effectively addressing the bottleneck of driving range and providing a more flexible solution for sustainable transportation.

[0003] During the operation of an electric vehicle, the system output voltage often fluctuates due to the significant change in the coupling coefficient of the energy transfer coil as the vehicle moves. Although various control methods have been proposed for controlling the output voltage of wireless charging systems for electric vehicles, the following shortcomings still exist:

[0004] First, existing wireless charging control methods fail to effectively suppress output voltage fluctuations during dynamic wireless charging. These methods primarily rely on feedback control of the measurement signal; however, feedback control cannot suppress disturbances promptly and completely. In dynamic wireless charging systems, the coupling coefficients of the transceiver coils often vary significantly, compounded by external interference from a strong magnetic field environment. These factors pose a significant challenge to the system's output voltage control.

[0005] Secondly, existing output voltage control methods for dynamic wireless charging systems for electric vehicles typically require multiple voltage, current, or coupling coefficient sensors to acquire system status information. These additional sensors not only significantly increase installation costs but also raise the risk of system failure. Furthermore, the subsequent maintenance costs of the system rise significantly with the increase in the number of sensors. Therefore, designing an adaptive control method based on low sensor requirements is more advantageous for handling complex wireless charging application scenarios.

[0006] Third, existing control methods fail to adequately address the adverse effects of sensor measurement noise on system performance. Measurement noise affects the accuracy of the controller. In traditional active disturbance rejection control structures, the use of high-gain extended state observers further amplifies the impact of measurement noise, leading to high-frequency jitter in the control signal and output voltage. This deficiency not only increases the energy consumption of the dynamic wireless charging system but also accelerates actuator wear and shortens the system's lifespan. Summary of the Invention

[0007] To overcome the technical challenges faced by current control methods for electric vehicle wireless charging systems, this invention proposes a voltage control method and system for dynamic wireless charging systems based on adaptive filters. This invention not only precisely controls the output voltage of the wireless charging system but also effectively suppresses voltage fluctuations and high-frequency jitter during dynamic charging. By employing adaptive input gain identification technology, the need for additional sensors is eliminated, significantly reducing the system's implementation cost. This invention, through its innovative control scheme, substantially improves the performance of electric vehicles performing dynamic wireless charging in complex environments.

[0008] To achieve the above objectives, the present invention adopts the following technical solution:

[0009] I. A Control Method for Wireless Charging System of Electric Vehicles Based on Adaptive Voltage Filter

[0010] First, an active disturbance rejection control (ADRC) model is constructed. The desired output voltage value is given as the input signal to the ADRC model, and the control signal μ output by the ADRC model is applied to the electric vehicle dynamic wireless charging system. Next, an adaptive filter is constructed. The output voltage measurement signal V1* of the electric vehicle dynamic wireless charging system is sent to the adaptive filter. The adaptive filter, combined with the control signal μ, generates a predicted output voltage value V1 and sends it to the ADRC model. The ADRC model estimates the disturbance based on the predicted output voltage value and obtains an estimate of the derivative of the predicted output voltage value. And the estimated value of the total system disturbance Then, by combining the control signal μ, the estimated value of the derivative of the predicted output voltage is obtained. After online input gain identification based on the estimated total system disturbance, the system input gain is obtained. It is then fed back to the active disturbance rejection control model to complete the voltage control of the dynamic wireless charging system for electric vehicles.

[0011] The active disturbance rejection control model includes an extended state observer and an active disturbance rejection control law; the extended state observer satisfies the following formula:

[0012]

[0013] Where V1 represents the predicted output voltage obtained through the adaptive filter, V2 represents the derivative of the predicted output voltage V1, and σ represents the total system disturbance. These represent the estimated values ​​of the predicted output voltage. Estimate of the derivative of the predicted output voltage And the estimated value of the total system disturbance The derivative of ω0 represents the positive definite observer gain coefficient;

[0014] The active disturbance rejection control law module satisfies the following formula:

[0015]

[0016] Among them, K c1 ,K c2 V1 represents the positive definite first constant gain and the second constant gain, respectively. r This indicates the desired output voltage value.

[0017] The estimated value of the derivative of the output voltage prediction with respect to the combined control signal μ. After online input gain identification based on the estimated total system disturbance, the system input gain is obtained. Specifically, the following formula is used for online input gain identification:

[0018]

[0019] in, K represents the input gain to be updated. c ε0 represents the input gain update error, where ε represents the update error. The estimated value of the derivative of the predicted output voltage. The derivative, P represents the state transition parameter to be updated. k λ represents the updated state transition parameters, and λ represents the forgetting factor.

[0020] The formula for the adaptive filter is as follows:

[0021]

[0022] in, This represents the updated predicted actual system state value; I1 and V1 represent the updated predicted actual current and output voltage values, respectively; T represents the transpose of the matrix; and A0 represents the state gain for adjusting the state information. V1 represents the predicted voltage state to be updated; A1 represents the control gain of the adjustment control signal; μ represents the output control signal; V1 * C represents the output voltage measurement signal of a dynamic wireless charging system, measured by a voltage sensor. m Let C be a constant gain matrix. m =[1,0], K p P represents the predicted gain. k-1 P represents the state error covariance to be updated. k Let R represent the updated state error covariance, R represent the measurement noise variance, and I2 represent the identity matrix of size 2. Q represents prior information about the covariance matrix; p This represents the state transition covariance.

[0023] II. A Control System for a Wireless Charging System for Electric Vehicles Based on an Adaptive Voltage Filter

[0024] The control system includes an online input gain identification module, an adaptive filter module, and an active disturbance rejection control unit;

[0025] The control signal μ output by the active disturbance rejection control unit is sent to the online input gain identification module, the electric vehicle dynamic wireless charging system, and the adaptive filter module. The active disturbance rejection control unit also sends an estimate of the derivative of the output voltage prediction value. And the estimated value of the total system disturbance The input gain is sent to the online input gain identification module, which outputs the system input gain. The output voltage prediction value V1 output by the adaptive filter module is sent to the active disturbance rejection control unit and the adaptive filter module. The output voltage measurement signal V1 of the electric vehicle dynamic wireless charging system is then sent to the active disturbance rejection control unit. * The voltage is sent to the adaptive filter module to complete the voltage control of the dynamic wireless charging system for electric vehicles.

[0026] The active disturbance rejection control unit includes an extended state observer module and an active disturbance rejection control law module. The adaptive filter module sends the predicted output voltage value V1 to the extended state observer module, and the online input gain identification module identifies the system input gain. The signal is sent to the extended state observer module and the active disturbance rejection control law module. The output of the active disturbance rejection control law module is recorded as the control signal μ and sent to the extended state observer module. The extended state observer module estimates the predicted value of the output voltage. Estimate of the derivative of the predicted output voltage And the estimated value of the total system disturbance The estimated value of the derivative of the predicted output voltage is sent to the active disturbance rejection control law module, and the extended state observer module sends the estimated value of the derivative of the predicted output voltage. And the estimated value of the total system disturbance

[0027] III. A computer device

[0028] The computer device includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the steps of the control method for the electric vehicle wireless charging system based on an adaptive voltage filter.

[0029] IV. A computer-readable storage medium

[0030] The medium stores a computer program, which, when executed by a processor, implements the steps of the control method for the electric vehicle wireless charging system based on an adaptive voltage filter.

[0031] V. A computer program product

[0032] The product includes a computer program / instructions that, when executed by a processor, implement the steps of the control method for the electric vehicle wireless charging system based on an adaptive voltage filter.

[0033] Compared with the prior art, the present invention has the following significant advantages:

[0034] First, this invention fully considers the application scenarios of dynamic wireless charging. By introducing an extended state observer, it effectively addresses the complex uncertainties and external disturbances in dynamic wireless charging systems. This technological innovation provides the controller with stronger anti-interference capabilities and significantly improves the system's stability in the face of various disturbances.

[0035] Second, this invention employs a total disturbance model and online parameter identification technology, eliminating the reliance on additional input voltage, current sensors, and coupling coefficient sensors. The proposed method requires only a single voltage sensor to achieve precise control of the output voltage. This innovation not only significantly reduces implementation and maintenance costs but also enhances the system's adaptability to complex environments.

[0036] Third, through the design of an adaptive filter, this invention effectively eliminates the interference of sensor measurement noise on the system, overcoming the measurement noise amplification problem caused by the high-gain characteristics of traditional extended state observers. This technology not only improves controller performance but also avoids additional energy consumption and excessive wear of the actuator, further enhancing the stability and lifespan of the dynamic wireless charging system. Attached Figure Description

[0037] Figure 1 This is a diagram of the designed active disturbance rejection control structure based on an adaptive voltage filter.

[0038] Figure 2 This is a diagram showing the effect of total disturbance estimation for a dynamic wireless charging system.

[0039] Figure 3 This is a diagram showing the effect of controlling the output signal.

[0040] Figure 4 This is a diagram showing the effect of online input gain identification.

[0041] Figure 5 This is a diagram showing the output voltage filtering effect of a dynamic wireless charging system. Detailed Implementation

[0042] The present invention will now be described in detail with reference to the accompanying drawings.

[0043] The dynamic wireless charging system for electric vehicles proposed in this invention adopts an active disturbance rejection control structure based on an adaptive filter, such as... Figure 1 As shown. This system can not only precisely control the output voltage of the wireless charging system, but also effectively suppress voltage fluctuations and high-frequency jitter during dynamic charging. The adaptive input gain identification module eliminates the need for additional sensors, significantly reducing the system's implementation cost. Its components include an online input gain identification module, an adaptive filter module, an active disturbance rejection control unit, and a voltage sensor; specifically:

[0044] The control signal μ output by the active disturbance rejection control unit is sent to the online input gain identification module, the electric vehicle dynamic wireless charging system, and the adaptive filter module. The active disturbance rejection control unit also sends an estimate of the derivative of the output voltage prediction value. And the estimated value of the total system disturbance The input gain is sent to the online input gain identification module, which outputs the system input gain. The extended state observer module, the active disturbance rejection control law module, and the adaptive filter module of the active disturbance rejection control unit are sent to the active disturbance rejection control unit. The output voltage prediction value V1 output by the adaptive filter module is sent to the extended state observer module of the active disturbance rejection control unit. The output voltage measurement signal V1 of the dynamic wireless charging system of the electric vehicle is obtained by measuring the voltage signal through the voltage sensor. * The voltage is sent to the adaptive filter module to complete the voltage control of the dynamic wireless charging system for electric vehicles.

[0045] The active disturbance rejection control unit includes an extended state observer module and an active disturbance rejection control law module. The adaptive filter module sends the predicted output voltage value V1 to the extended state observer module, and the online input gain identification module identifies the system input gain. The signal is sent to the extended state observer module and the active disturbance rejection control law module. The output of the active disturbance rejection control law module is recorded as the control signal μ and sent to the extended state observer module. The extended state observer module estimates the predicted value of the output voltage. Estimate of the derivative of the predicted output voltage And the estimated value of the total system disturbance The estimated value of the derivative of the predicted output voltage is sent to the active disturbance rejection control law module, and the extended state observer module sends the estimated value of the derivative of the predicted output voltage. And the estimated value of the total system disturbance

[0046] This invention also proposes an adaptive voltage filtering and control method for a dynamic wireless charging system for electric vehicles. This control method aims to achieve accurate tracking of the output voltage to the desired voltage signal while effectively filtering sensor measurement noise. Its control objective is to achieve stable control of the desired output voltage while satisfying the given equations, and to effectively suppress voltage and control signal jitter during dynamic wireless charging. The control method specifically includes the following steps:

[0047] First, an active disturbance rejection control (ADRC) model is constructed. The desired output voltage value is given as the input signal to the ADRC model, and the control signal μ output by the ADRC model is applied to the dynamic wireless charging system for electric vehicles. Next, an adaptive filter is constructed, and the output voltage measurement signal V1 of the dynamic wireless charging system for electric vehicles is used. * The signal is sent to an adaptive filter, which, combined with the control signal μ, generates a predicted output voltage value and sends it to the active disturbance rejection control (ADRC) model. The ADRC model estimates the disturbance based on the predicted output voltage value and obtains an estimate of the derivative of the predicted output voltage value. And the estimated value of the total system disturbance Then, by combining the control signal μ, the estimated value of the derivative of the predicted output voltage is obtained. After online input gain identification based on the estimated total system disturbance, the system input gain is obtained. It is then fed back to the active disturbance rejection control model to complete the voltage control of the dynamic wireless charging system for electric vehicles.

[0048] The control circuit of a dynamic wireless charging system for electric vehicles is described by the following set of differential equations:

[0049]

[0050] Among them, V in L represents an unknown input voltage. d C represents the circuit inductance. d2 R represents the circuit capacitance. L I represents the load resistance. Ld Indicates the flow through inductor L d The current, V out The output voltage is represented by μ, and the system control signal is represented by μ. These represent the inductor current I. Ld and output voltage V out Differentials with respect to time.

[0051] The active disturbance rejection control model includes an extended state observer and an active disturbance rejection control law; the extended state observer satisfies the following formula:

[0052]

[0053] Where V1 represents the predicted output voltage obtained through the adaptive filter, V2 represents the derivative of the predicted output voltage V1, and σ represents the total system disturbance. These represent the estimated values ​​of the predicted output voltage. Estimate of the derivative of the predicted output voltage And the estimated value of the total system disturbance The derivative of ω0 represents the positive definite observer gain coefficient;

[0054] The active disturbance rejection control law module satisfies the following formula:

[0055]

[0056] Among them, K c1 ,K c2 V1 represents the positive definite first constant gain and the second constant gain, respectively. r This indicates the desired output voltage value.

[0057] The estimated value of the derivative of the predicted output voltage with respect to the control signal μ. After online input gain identification based on the estimated total system disturbance, the system input gain is obtained. Specifically, the following formula is used for online input gain identification:

[0058]

[0059] in, K represents the input gain to be updated. c ε0 represents the input gain update error, where ε represents the update error. The estimated value of the derivative of the predicted output voltage. The derivative, P represents the state transition parameter to be updated. k Let represent the updated state transition parameters, and λ represent the forgetting factor. The system input gain is obtained through this formula. Get online updates.

[0060] The formula for an adaptive filter is as follows:

[0061]

[0062] in, This represents the updated predicted actual system state value; I1 and V1 represent the updated predicted actual current and output voltage values, respectively; T represents the transpose of the matrix; and A0 represents the state gain for adjusting the state information. V1 represents the predicted voltage state to be updated; A1 represents the control gain of the adjustment control signal; μ represents the output control signal; V1 * C represents the output voltage measurement signal of a dynamic wireless charging system, measured by a voltage sensor. m Let C be a constant gain matrix. m =[1,0], K p P represents the predicted gain. k-1 P represents the state error covariance to be updated. k Let R represent the updated state error covariance, R represent the measurement noise variance, and I2 represent the identity matrix of size 2. Q represents prior information about the covariance matrix; p This represents the state transition covariance.

[0063] The solution proposed in this invention is expected to overcome the challenges of voltage control in current wireless charging systems for electric vehicles, improve system performance and stability, and reduce hardware costs, providing a more reliable solution for power transmission in electric vehicles.

[0064] The experimental results of this embodiment are as follows: Figures 2 to 5As shown, ADRC represents the traditional active disturbance rejection control method without a filter, LPFC represents the active disturbance rejection control method combined with a traditional low-pass filter, PBC adopts an active disturbance rejection control method based on an improved filter structure, and AKFC is an active disturbance rejection control method based on an adaptive filter. Compared with the PBC method, the main difference of AKFC is that it designs an online input gain identification module, which can realize adaptive filtering and control and eliminate the dependence on additional sensors.

[0065] Figure 2 The effectiveness of the extended state observer in estimating the total disturbance is demonstrated. Regardless of how the disturbance changes during dynamic wireless charging, the extended state observers used in all four control methods can accurately estimate the total disturbance. However, because the traditional ADRC method does not introduce a filter, the observation information contains high-frequency jitter, which is transmitted through the control law, causing high-frequency oscillations in the control signal. Figure 3 The effects of four control signal methods were demonstrated, among which... Figure 3 The value of 'a' indicates that traditional ADRC generates excessive high-frequency chatter, which increases actuator energy consumption and wear. Figure 3 b, Figure 3 c and Figure 3 The values ​​of d indicate that the LPFC, PBC, and AKFC methods (i.e., the methods of this invention) successfully suppressed this jitter due to the introduction of filters. Figure 4 The effectiveness of the AKFC method (i.e., the method of this invention) in online input gain identification is demonstrated. During dynamic wireless charging, the system input gain changes significantly, but the proposed method can accurately identify the time-varying input gain. Furthermore, Figure 5 a, Figure 5 b, Figure 5 c and Figure 5 Figure d shows the output voltage control and filtering effects of the four methods during dynamic wireless charging. Compared with the traditional ADRC, AKFC successfully achieves noise filtering of the output voltage and suppresses voltage fluctuations during dynamic charging. Furthermore, compared with LPFC and PBC methods, the proposed method achieves output voltage fluctuation suppression during dynamic wireless charging, realizing a stable and continuous voltage output. In contrast, LPFC and PBC methods generate larger voltage fluctuations and struggle to maintain a stable voltage output. These results demonstrate that the proposed method effectively suppresses output voltage fluctuations during dynamic wireless charging while achieving sensor noise filtering. The experimental figures strongly support the effectiveness and superior performance of the invention and further demonstrate the broad application potential of the proposed adaptive voltage filtering and control method in electric vehicle wireless charging systems.

[0066] This invention is not limited to this embodiment. Any equivalent concept or modification within the technical scope disclosed in this invention shall be included within the protection scope of this invention.

Claims

1. A control method for a wireless charging system for electric vehicles based on an adaptive voltage filter, characterized in that, Includes the following steps: First, an active disturbance rejection control (ADRC) model is constructed. The desired output voltage value is given as the input signal to the ADRC model, and the output control signal of the ADRC model is... This is applied to a dynamic wireless charging system for electric vehicles; subsequently, an adaptive filter is constructed, and the output voltage measurement signal of the dynamic wireless charging system for electric vehicles is used. The signal is sent to an adaptive filter, which then combines the control signal with the adaptive filter. Generate predicted output voltage The data is then sent to the active disturbance rejection control (ADRC) model. The ADRC model estimates the disturbance based on the predicted output voltage and obtains an estimate of the derivative of the predicted output voltage. And the estimated value of the total system disturbance ; Then, combined with control signals The estimated value of the derivative of the predicted output voltage. After online input gain identification based on the estimated total system disturbance, the system input gain is obtained. It is then fed back to the active disturbance rejection control model to complete the voltage control of the dynamic wireless charging system for electric vehicles; The active disturbance rejection control model includes an extended state observer and an active disturbance rejection control law module; the extended state observer satisfies the following formula: in, This represents the predicted output voltage obtained through the adaptive filter. Indicates the predicted output voltage value The derivative of This represents the total system disturbance. These represent the estimated values ​​of the predicted output voltage. Estimate of the derivative of the predicted output voltage And the estimated value of the total system disturbance The derivative of This represents the positive definite observer gain coefficient; The active disturbance rejection control law module satisfies the following formula: in, Let these represent the positive definite first constant gain and the second constant gain, respectively. This indicates the desired output voltage value.

2. The control method for a wireless charging system for electric vehicles based on an adaptive voltage filter according to claim 1, characterized in that, The combined control signal The estimated value of the derivative of the predicted output voltage. After online input gain identification based on the estimated total system disturbance, the system input gain is obtained. Specifically, the following formula is used for online input gain identification: in, This indicates the input gain to be updated. This indicates the update of the error gain. This represents the input gain update error. The estimated value of the derivative of the predicted output voltage. The derivative, This indicates the state transition parameters to be updated. This represents the updated state transition parameters. This represents the forgetting factor.

3. The control method for a wireless charging system for electric vehicles based on an adaptive voltage filter according to claim 1, characterized in that, The formula for the adaptive filter is as follows: in, This represents the updated predicted value of the actual system state. These represent the updated predicted values ​​of the actual current and the predicted value of the output voltage, respectively. Represents the transpose of a matrix; This represents the state gain that adjusts the state information. This represents the predicted voltage state value to be updated. This indicates the control gain of the adjustment control signal; This indicates the output control signal. This represents the output voltage measurement signal of the dynamic wireless charging system, as measured by a voltage sensor. Let the constant gain matrix satisfy the following condition: , Indicates the predicted gain. This represents the state error covariance to be updated. This represents the updated state error covariance. Indicates the variance of measurement noise. Represents an identity matrix of size 2; Represents prior information about the covariance matrix; This represents the state transition covariance.

4. A control system for a wireless charging system for electric vehicles based on an adaptive voltage filter, characterized in that, It includes an online input gain identification module, an adaptive filter module, and an active disturbance rejection control unit; The control signal output by the active disturbance rejection control unit The active disturbance rejection control unit also sends the estimated value of the derivative of the output voltage prediction value to the input gain online identification module, the electric vehicle dynamic wireless charging system, and the adaptive filter module. And the estimated value of the total system disturbance The input gain is sent to the online input gain identification module, which outputs the system input gain. The predicted output voltage is sent to the active disturbance rejection control unit and the adaptive filter module. The output voltage measurement signal of the dynamic wireless charging system for electric vehicles is sent to the active interference rejection control unit. The voltage is sent to the adaptive filter module to complete the voltage control of the dynamic wireless charging system for electric vehicles. The active disturbance rejection control unit includes an extended state observer module and an active disturbance rejection control law module. The adaptive filter module outputs the predicted voltage value. The input gain is sent to the extended state observer module, and the online input gain identification module identifies the system input gain. The signal is sent to the extended state observer module and the active disturbance rejection control law module. The output of the active disturbance rejection control law module is denoted as the control signal. And send it to the extended state observer module, which will then send the estimated value of the output voltage prediction. Estimate of the derivative of the predicted output voltage And the estimated value of the total system disturbance The estimated value of the derivative of the predicted output voltage is sent to the active disturbance rejection control law module, and the extended state observer module sends the estimated value of the derivative of the predicted output voltage. And the estimated value of the total system disturbance .

5. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the control method for an electric vehicle wireless charging system based on an adaptive voltage filter as described in any one of claims 1 to 3.

6. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the control method for an electric vehicle wireless charging system based on an adaptive voltage filter as described in any one of claims 1 to 3.

7. A computer program product comprising a computer program / instructions, characterized in that, When the computer program / instructions are executed by the processor, they implement the steps of the control method for a wireless charging system for electric vehicles based on an adaptive voltage filter as described in any one of claims 1 to 3.

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