Method and system for output power control based on dynamic wireless charging of electric vehicles

Abstract

The application discloses an output power control method and system based on dynamic wireless charging of an electric vehicle, relates to the technical field of wireless power transmission, and aims to solve the output fluctuation problem of an electric vehicle wireless charging system caused by rapid mutual inductance change. The method establishes a linear parameter time-varying model, identifies model parameters by using an auxiliary variable method, and then designs a robust feedback controller and a feedforward controller, so that stable control of system output is realized without additional hardware support. The application effectively improves the stability of output voltage and the anti-interference ability of the system in the dynamic wireless charging process, enhances charging safety and flexibility, and is suitable for the dynamic energy supplementing scene in the driving process of the electric vehicle.

Description

Technical Field

[0001] This invention relates to the field of wireless power transmission technology, and in particular to an output power control method and system based on dynamic wireless charging of electric vehicles. Background Technology

[0002] Compared to traditional wired charging, wireless charging technology eliminates the need for electrical plugging and unplugging, improves the ease of use of charging equipment, and increases the flexibility of charging infrastructure, providing strong support for the development of the electric vehicle market. In particular, dynamic wireless charging technology for electric vehicles allows vehicles to replenish their power while driving, effectively reducing battery load capacity, decreasing overall vehicle weight, alleviating range anxiety, and promoting the development of green and sustainable transportation.

[0003] However, in the dynamic wireless charging scenario for electric vehicles, the relative positions of the transmitting and receiving coils continuously change during vehicle operation, causing the system's mutual inductance to fluctuate continuously. This, coupled with load fluctuations, presents a significant challenge to the stable control of the charging system's output voltage. Existing technologies suffer from the following drawbacks: traditional component parameter-based modeling methods require measuring all system component parameters, leading to high modeling difficulty; linear small-signal models cannot accurately describe the system's output characteristics under large-scale mutual inductance variations; and under scenarios of periodic mutual inductance fluctuations and load fluctuations, the controller's robustness and anti-interference capabilities are insufficient, making it difficult to guarantee output voltage stability and impacting charging safety and user experience. Therefore, there is an urgent need for a method and device capable of achieving stable output power control under dynamic mutual inductance variations. Summary of the Invention

[0004] The present invention aims to solve at least one of the technical problems existing in the prior art, and proposes an output power control method and system based on dynamic wireless charging of electric vehicles.

[0005] In a first aspect, embodiments of the present invention provide an output power control method based on dynamic wireless charging of electric vehicles, characterized in that it includes:

[0006] Establish a linear parameter time-varying model Gs between the duty cycle and output voltage of the Buck circuit after dynamic wireless charging of electric vehicles, and a model Gd between the input voltage and output voltage of the Buck circuit, and determine the order of the models Gs and Gd.

[0007] The parameters of the models Gs and Gd are identified based on the auxiliary variable method.

[0008] Based on the identified models Gs and Gd, a feedback controller Gc and a feedforward controller Gf are designed respectively. The controller is adjusted according to the reference voltage to achieve constant voltage output of the system under dynamic charging.

[0009] Furthermore, the standard forms of the linear parameter time-varying models Gs and Gd are:

[0010]

[0011] Where x(t) represents the noiseless output of the system, u(t) represents the system input, e(t) represents the system noise, y(t) represents the noisy output of the system, and p t =p( t ) represents the scheduling variable, s represents the differential operator, and H and M represent polynomials in terms of p(t) and s.

[0012] Furthermore, the specific expressions for polynomials H and M are as follows:

[0013]

[0014] Where n h n m The order of the polynomials in the denominator and numerator of the transfer function, n m <n h , The polynomial representing the denominator coefficients of the transfer function. The polynomial representing the numerator coefficients of the transfer function.

[0015] Furthermore, the orders of models Gs and Gd are determined by means of: applying a step signal of preset amplitude to the duty cycle of the Buck circuit in the dynamic wireless charging system for electric vehicles and obtaining the system output curve; if the output curve does not oscillate, the system is fitted based on the first-order model; if the output curve oscillates, the system is fitted based on the second-order or higher-order model.

[0016] Furthermore, the parameters of the models Gs and Gd are identified based on the auxiliary variable method, specifically including:

[0017] Initial values ​​for the model's parameter vector (0) and the number of iterations λ are set;

[0018] Noise-free auxiliary variables are generated based on the auxiliary model. , for u(t) k ), y(t) k )and A continuous filter is used for filtering to generate a filtered regression vector. and auxiliary vector , Let y represent the system output and u represent the system input at discrete sampling points t=kTs.

[0019] Iteratively update the parameter vector according to the parameter update formula. The identification process stops when the number of iterations reaches the upper limit or the parameter vector converges.

[0020] Furthermore, the specific method for designing the feedback controller Gc includes: based on the normalized coprime factorization theory, the model Gs is expressed as an H-infinite transfer function with multiplicative uncertainty, weight functions W1 and W2 are selected, and the optimal H-infinite controller Ks is obtained by minimizing the H-infinite cost function. The feedback controller form is Gc = W1KsW2.

[0021] Furthermore, the specific method for designing the feedforward controller Gf includes: based on the transfer function from the disturbance to the output, setting the numerator of the transfer function to zero to obtain the expression for the feedforward controller Gf, and dynamically adjusting the gain of Gf according to the output voltage collected by the system in real time.

[0022] Secondly, this invention also discloses an output power control system based on dynamic wireless charging for electric vehicles, comprising: a model generation module, a model identification module, and a power control module; wherein:

[0023] The model generation module is used to establish a linear parameter time-varying model Gs between the duty cycle and output voltage of the Buck circuit after dynamic wireless charging of electric vehicles, and a model Gd between the input voltage and output voltage of the Buck circuit, and to determine the order of the models Gs and Gd.

[0024] The model identification module is used to identify the parameters of the models Gs and Gd based on the auxiliary variable method.

[0025] The power control module is used to design a feedback controller Gc and a feedforward controller Gf based on the identified models Gs and Gd, respectively, and adjust the controllers according to the reference voltage to achieve constant voltage output of the system under dynamic charging.

[0026] Thirdly, the present invention discloses an electronic device, comprising:

[0027] One or more processors;

[0028] Memory, used to store one or more programs;

[0029] When the one or more programs are executed by the one or more processors, the one or more processors implement the control method.

[0030] A computer-readable medium having a computer program stored thereon, the computer program implementing the steps of the method when executed by a processor.

[0031] This invention discloses an output power control method and device for dynamic wireless charging of electric vehicles, aiming to solve the output fluctuation problem caused by rapid changes in mutual inductance in electric vehicle wireless charging systems. The method establishes a time-varying linear parameter model, uses an auxiliary variable method to identify model parameters, and then designs a robust feedback controller and a feedforward controller to achieve stable system output control without additional hardware support. This invention effectively improves the stability of output voltage and the system's anti-interference capability during dynamic wireless charging, enhances charging safety and flexibility, and is suitable for dynamic energy replenishment scenarios during electric vehicle operation.

[0032] Compared with the prior art, the present invention has the following beneficial effects:

[0033] 1. High modeling accuracy and low difficulty: This invention adopts a linear parameter time-varying model (Gs and Gd), which does not require measuring all the parameters of the system components. It can accurately describe the system output characteristics under a wide range of mutual inductance changes through a data-driven approach, which greatly reduces the modeling difficulty compared with traditional modeling methods.

[0034] 2. Reliable parameter identification: This invention uses the auxiliary variable method to identify model parameters, which effectively suppresses the influence of system noise on the identification results and improves the accuracy and reliability of parameter identification;

[0035] 3. Excellent control performance: This invention combines robust feedback control and feedforward control to form a composite control strategy. The feedback controller can cope with the uncertainties caused by mutual inductance fluctuations and load fluctuations, ensuring the robustness of the system; the feedforward controller can compensate for input voltage disturbances caused by mutual inductance changes in advance, improving the dynamic response speed of the system. The synergistic effect of the two significantly suppresses output voltage fluctuations.

[0036] 4. High safety and flexibility: The stable output voltage of this invention ensures the safety of the charging process, making it suitable for dynamic energy replenishment scenarios during electric vehicle operation. It provides users with a more flexible charging experience and helps promote the application of dynamic wireless charging technology. Attached Figure Description

[0037] Figure 1 A flowchart illustrating an output power control method for dynamic wireless charging of electric vehicles provided in an embodiment of the present invention;

[0038] Figure 2 This is a control block diagram for normalized coprime factor decomposition provided in an embodiment of the present invention;

[0039] Figure 3 This is a feedforward-control block diagram provided for an embodiment of the present invention;

[0040] Figure 4 A comparison of voltage waveforms before and after adding feedforward control at different rotational speeds, provided for embodiments of the present invention;

[0041] Figure 5 This is a structural block diagram of an output power control system based on dynamic wireless charging for electric vehicles provided in an embodiment of the present invention;

[0042] Figure 6 This is a structural block diagram of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0043] To enable those skilled in the art to better understand the technical solutions of the present invention, exemplary embodiments of the present invention are described below in conjunction with the accompanying drawings, including various details of the embodiments of the present invention to aid understanding. These should be considered merely exemplary. Therefore, those skilled in the art should recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of the present invention. Similarly, for clarity and brevity, descriptions of well-known functions and structures are omitted in the following description.

[0044] Where there is no conflict, the various embodiments of the present invention and the features thereof may be combined with each other.

[0045] As used herein, the term “and / or” includes any and all combinations of one or more related enumerated entries.

[0046] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the invention. As used herein, the singular forms “a” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will also be understood that when the terms “comprising” and / or “made of” are used in this specification, the presence of the stated feature, integral, step, operation, element, and / or component is specified, but the presence or addition of one or more other features, integrals, steps, operations, elements, components, and / or groups thereof is not excluded. Terms such as “connected” or “linked” are not limited to physical or mechanical connections but can include electrical connections, whether direct or indirect.

[0047] Unless otherwise specified, all terms used herein (including technical and scientific terms) have the same meaning as commonly understood by one of ordinary skill in the art. It will also be understood that terms such as those defined in commonly used dictionaries should be interpreted as having the meaning consistent with their meaning in the context of the relevant art and the invention, and will not be interpreted as having an idealized or overly formal meaning unless expressly so defined herein.

[0048] In the technical solution of this invention, the collection, storage, use, processing, transmission, provision, and disclosure of user personal information all comply with relevant laws and regulations and do not violate public order and good morals. The use of user data in this technical solution follows relevant national laws and regulations (e.g., the "Information Security Technology - Personal Information Security Specification"). For example: appropriate measures are taken for personal information access control; restrictions are imposed on the display of personal information; the purpose of using personal information does not exceed the scope of direct or reasonable association; and explicit identity targeting is eliminated when using personal information to avoid precisely locating a specific individual.

[0049] To address at least one of the technical problems existing in the aforementioned related technologies, the present invention provides an output power control method and system based on dynamic wireless charging for electric vehicles.

[0050] This implementation discloses an output power control method based on dynamic wireless charging for electric vehicles, such as... Figure 1 ,include:

[0051] S100. Establish a linear time-varying model Gs of the Buck circuit after dynamic wireless charging of electric vehicles, which is related to the duty cycle and output voltage, and a model Gd of the Buck circuit, which is related to the input voltage and output voltage. Determine the order of the models Gs and Gd. The Buck circuit (step-down chopper circuit) is a DC-DC power converter that reduces the input DC voltage to a lower stable DC output voltage by periodically controlling the switching transistor (such as MOSFET) to turn on and off, in conjunction with the energy storage and filtering effects of inductors and capacitors.

[0052] In this embodiment, the standard forms of the linear parameter time-varying models Gs and Gd are:

[0053] (1)

[0054] Where x(t) represents the noiseless output of the system, u(t) represents the system input, e(t) represents the system noise, y(t) represents the noisy output of the system, and p t =p( t ) represents the scheduling variable, s represents the differential operator, and H and M represent polynomials in terms of p(t) and s; the specific expressions for polynomials H and M are:

[0055] (2)

[0056] Where n h n m The order of the polynomials in the denominator and numerator of the transfer function, n m <n h , The polynomial representing the denominator coefficients of the transfer function. The polynomial representing the numerator coefficients of the transfer function.

[0057] Specifically, h i (·) and m j (·) Expanding, we get:

[0058] (3)

[0059] Where {f l} and {g l} is about p t polynomial, {f l}、{g l The specific form and order n of} α n β This is related to the model structure. The parameters to be identified in the polynomial are written in vector form:

[0060] (4)

[0061] in:

[0062] (5)

[0063] In this embodiment, the order of model Gs and model Gd is determined by applying a step signal of preset amplitude to the duty cycle of the Buck circuit of the electric vehicle dynamic wireless charging system to obtain the system output curve; if the output curve does not oscillate, the system is fitted based on the first-order model; if the output curve oscillates, the system is fitted based on the second-order or higher-order model.

[0064] S200. Identify the parameters of the models Gs and Gd based on the auxiliary variable method; in this embodiment, the parameters of the models Gs and Gd are identified based on the auxiliary variable method, and the specific method includes:

[0065] S201. Initial values ​​for the model's parameter vectors (0) and the number of iterations λ are set;

[0066] S202. Generate noise-free auxiliary variables based on the auxiliary model. , for u(t) k ), y(t) k )and A continuous filter is used for filtering to generate a filtered regression vector. and auxiliary vector , Let y represent the system output and u represent the system input at discrete sampling points t=kTs.

[0067] S203. Iteratively update the parameter vector according to the parameter update formula. The identification process stops when the number of iterations reaches the upper limit or the parameter vector converges.

[0068] Specifically, model identification requires finding the model parameter vector θ to fit the sampled data D. N ={y(t k ),u(t k ),p(t k (N represents the number of sampled data, t) k This means that at t=kT s Discrete sampling points (where y represents system output, u represents system input, and p represents scheduling variables), i.e., minimizing based on D N The mean square prediction error.

[0069] The identification steps are as follows:

[0070] Set the initial value of the parameter vector θˆ(0) to 10. 6 ×[1,1,...]1×(n m +n h The number of iterations λ is set to 1.

[0071] Noise-free auxiliary variables are generated based on the auxiliary model. For u(t) k ), y(t) k )and A continuous filter V is used for filtering to generate a filtered regression vector. and auxiliary vector :

[0072] (6)

[0073] Update the parameter vector according to the following formula. :

[0074] (7)

[0075] When the number of iterations reaches the upper limit or If convergence has been achieved, the identification process stops. Otherwise, λ = λ + 1 and continue iterating.

[0076] S300. Based on the identified models Gs and Gd, a feedback controller Gc and a feedforward controller Gf are designed respectively. The controller is adjusted according to the reference voltage to achieve constant voltage output of the system under dynamic charging.

[0077] In this embodiment, the specific method for designing the feedback controller Gc includes: based on the normalized coprime factorization theory, the model Gs is expressed as an H-infinite transfer function with multiplicative uncertainty, weight functions W1 and W2 are selected, and the optimal H-infinite controller Ks is obtained by minimizing the H-infinite cost function. The feedback controller form is Gc = W1KsW2.

[0078] Specifically, firstly, based on the model G identified in step 2... s Design a robust feedback controller K. Figure 2 This is a block diagram of robust control based on normalized coprime factorization, K. s W1 represents the controller based on coprime factorization, and W2 represents the post-compensator and the pre-compensator, respectively.

[0079] Based on the normalized coprime factorization theory, model G s It can be represented as:

[0080] (8)

[0081] In the formula, N(s) and H(s) are stable and regular transfer functions that satisfy the normalized coprime factor condition. Based on the identified model and the range of variation of the scheduling variables, G can be... s Rewritten in the form of an H-infinite transfer function containing multiplicative uncertainty:

[0082] (9)

[0083] in , , W is the mean of the scheduling variable. N and W H Weighting function for uncertainty:

[0084] (10)

[0085] Appropriate weighting functions W1 and W2 are selected to reflect the ideal trade-off between performance and robustness. The controller configuration adopted is K = W1K. s W2, where K s The optimal H∞ controller is obtained by minimizing the H∞ cost function.

[0086] (11)

[0087] In the formula:

[0088] (12)

[0089] In this embodiment, the specific method for designing the feedforward controller Gf includes: based on the transfer function from the disturbance to the output, setting the numerator of the transfer function to zero to obtain the expression for the feedforward controller Gf, and dynamically adjusting the gain of Gf according to the output voltage collected by the system in real time.

[0090] Specifically, the overall control block diagram of the system is as follows: Figure 3 As shown, this includes both feedforward and feedback controllers. The following are the design steps for the feedforward controller Gf:

[0091] The transfer function from interference to output can be expressed as:

[0092] (13)

[0093] Therefore, to eliminate the influence of interference on the output, the numerator of equation (12) should be equal to zero, so Gf(s) should be:

[0094] (14)

[0095] Since the model Gd(s) is time-varying, the gain of Gf(s) needs to be adjusted in real time. Therefore, as Figure 3 As shown by the red line in the diagram, during the control process, u o It is also collected at the same time to update Gf(s).

[0096] This embodiment discloses an output power control method and device based on dynamic wireless charging for electric vehicles, aiming to solve the output fluctuation problem caused by rapid changes in mutual inductance in electric vehicle wireless charging systems. The method establishes a time-varying linear parameter model, uses an auxiliary variable method to identify model parameters, and then designs a robust feedback controller and a feedforward controller to achieve stable system output control without additional hardware support. This invention effectively improves the stability of output voltage and the system's anti-interference capability during dynamic wireless charging, enhances charging safety and flexibility, and is suitable for dynamic energy replenishment scenarios during electric vehicle operation.

[0097] To better understand this embodiment, a typical wireless charging system for electric vehicles (the main parameters of the system are shown in Table I) will be used as an example for further explanation.

[0098] Table I. Experimental Equipment Parameters

[0099]

[0100] In this example, the specific steps include:

[0101] Step 1: Establish a linear time-varying parameter model G of the Buck circuit after dynamic wireless charging for electric vehicles, relating the duty cycle to the output voltage. s And the model G between Buck input voltage and output voltaged Determine model G s and G d The order of the model; specifically: determining the model G with Buck duty cycle as system input u, Buck input voltage as scheduling variable p1, and charging voltage as output y. s And the LPV model G with Buck input voltage as system input u, Buck duty cycle as scheduling variable p2, and charging voltage as output y. d .

[0102] First, determine the current operating frequency f of the electric vehicle wireless charging system. s and DC input voltage V d When f s =85kHz, V d When the input voltage is 300V, the static output voltage of the system is 120V. A step sequence is applied to the system input (i.e., the Buck duty cycle). Specifically, D is set to D=0.7 in the host computer, and the data is transmitted to the DSP chip via a T1J-Tag simulator. The DSP chip then transmits the signal to the FPGA chip on the circuit board to adjust the Buck duty cycle u(k). The voltage signal y(k) is acquired using an oscilloscope and transmitted to the host computer. A voltage waveform is generated using Matlab software. The waveform shows that when the system input step changes, the system output does not exhibit significant oscillation. Therefore, the first-order system G can be used as a basis for this analysis. s To fit the system, G d The method for determining the order of the system is similar, and a first-order model is also used for fitting.

[0103] Step 2, Identify Model G s and G d parameter:

[0104] Work point set =0.7. A pseudo-random binary sequence signal generated by a four-bit shift register is used as... To incentivize the system. The amplitude is ±0.05, and the shift period is 2ms. After executing the input injection command on the host computer, the oscilloscope at t k =kT s (k=1,2,...,N,T s Experimental data were sampled when the input voltage V was 3.2e−5 and N=1e5. The sampled data included the input voltage V. in and output voltage V o Then, the data is transmitted to the host computer for model identification. Based on the sampled D... N ={y(t k ),u(t k ),p(t k )}, Identify system model G sand interference model G d Set n h =n m =1, setting the initial value of the parameter vector. (0) is set to 10 6 ×[1,1,...]1×2, iteration count λ=1. Maximum iteration count λ max =1000. Then, based on equations (6) and (7), the auxiliary variables and parameter vectors are calculated. When the maximum number of iterations is reached, the algorithm is terminated to obtain the model parameters, thus the controlled object model G. s for:

[0105] (15)

[0106] After changing the input and scheduling variables, the model G of the perturbation channel is identified. d for:

[0107] (16)

[0108] Step 3, based on the identified model G s and G d Design feedback controller and feedforward controller G respectively. c and G f The system achieves constant voltage output under dynamic charging by adjusting the controller based on the reference voltage.

[0109] Based on Buck input voltage p1(t) k Substituting the range of variation of ) into equation (10), we can obtain N. nom and H nom for:

[0110] (17)

[0111] In this example, setting W1=3 / s and W2=1, the feedback controller G based on the normalized coprime factor can be calculated using Matlab R2023a. c (s) is:

[0112] (18)

[0113] Based on the zero-order hold method, the controller G c (s) is transformed from a continuous form to a discrete controller dG c For hardware programming:

[0114] (19)

[0115] Where z represents the difference operator. Furthermore, the feedforward controller G can be calculated according to equations (12) and (13). fDiscrete form feedforward controller dG f for:

[0116] (20)

[0117] Figure 4 The figure shows a comparison experiment of output fluctuation suppression before and after the addition of feedforward control. The purple line represents the input voltage of Buck, and the blue line represents the output voltage of Buck, i.e., the charging voltage. Figure 4 The image shows the output voltage control waveforms at speeds of 20, 30, 40, and 50 rad / min (≈10 km / h), where the sub- Figure 4 (a), (c), (e), and (g) represent the voltage waveforms under the action of only negative feedback control (without feedforward control loop). Figure 4 Figures (b), (d), (f), and (h) represent the voltage waveforms under the combined action of negative feedback control and feedforward control. As shown in the figures, the output voltage remains stable at the reference voltage of 100V at different speeds. However, when the input voltage V (represented by the purple line)... in When the voltage drops to its minimum value, i.e., when the receiving coil moves to the point where the transmitting coil switches, the output voltage V is only under the action of negative feedback control. o Significant disturbances will occur, as the rotational speed of the device increases, such as Figure 4 As shown in (a), (c), (e), and (g), the output voltage V o The fluctuations are becoming increasingly apparent.

[0118] Although feedback control can ensure the stability and robustness of the system, the real-time changes in the spatial positions of the transmitting and receiving coils cause changes in mutual inductance, leading to V... in Rapid changes are needed. To address the impact of this disturbance on the system promptly, a feedforward control loop is added to improve the system's dynamic performance, thereby effectively suppressing the output voltage V. o Fluctuations. For example... Figure 4 As shown in (b), (d), (f), and (h), the output voltage V increases with the increase of rotational speed. o No significant fluctuations were observed at different speeds. To quantitatively describe the control effect before and after adding feedforward control, V was calculated before and after adding feedforward control at different speeds. o The results of the OF (Output Fluctuation Factor) are shown in Table 2. It can be seen that after adding feedforward control, the output fluctuation factor OF decreases significantly, and the output voltage V... o The fluctuations were also significantly reduced, and the dynamic performance was significantly improved.

[0119] Table 2 Output fluctuation rate before and after adding feedforward control at different speeds

[0120]

[0121] Based on the same inventive concept, embodiments of the present invention also provide an output power control system based on dynamic wireless charging for electric vehicles, such as... Figure 5 It includes: a model generation module, a model identification module, and a power control module; wherein:

[0122] The model generation module is used to establish a linear parameter time-varying model Gs between the duty cycle and output voltage of the Buck circuit after dynamic wireless charging of electric vehicles, and a model Gd between the input voltage and output voltage of the Buck circuit, and to determine the order of the models Gs and Gd.

[0123] The model identification module is used to identify the parameters of the models Gs and Gd based on the auxiliary variable method.

[0124] The power control module is used to design a feedback controller Gc and a feedforward controller Gf based on the identified models Gs and Gd, respectively, and adjust the controllers according to the reference voltage to achieve constant voltage output of the system under dynamic charging.

[0125] The specific working methods of the model generation module, model identification module, and power control module have been described in detail in the above-mentioned output power control method based on dynamic wireless charging of electric vehicles, and will not be repeated here in this embodiment.

[0126] Based on the same inventive concept, embodiments of the present invention also provide an electronic device. Figure 6 This is a structural block diagram of an electronic device provided in an embodiment of the present invention. Figure 6 As shown, an embodiment of the present invention provides an electronic device including: one or more processors 101, a memory 102, and one or more I / O interfaces 103. The memory 102 stores one or more programs, which, when executed by the one or more processors, cause the one or more processors to implement any of the control methods described in the above embodiments; the one or more I / O interfaces 103 are connected between the processor and the memory, configured to enable information interaction between the processor and the memory.

[0127] The processor 101 is a device with data processing capabilities, including but not limited to a central processing unit (CPU); the memory 102 is a device with data storage capabilities, including but not limited to random access memory (RAM, more specifically SDRAM, DDR, etc.), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), and flash memory (FLASH); the I / O interface (read / write interface) 103 is connected between the processor 101 and the memory 102, and can realize information interaction between the processor 101 and the memory 102, including but not limited to a data bus (Bus).

[0128] In some embodiments, the processor 101, memory 102, and I / O interface 103 are interconnected via bus 104, and thus connected to other components of the computing device.

[0129] In some embodiments, the one or more processors 101 include a field-programmable gate array.

[0130] This invention also provides a computer-readable medium. The computer-readable medium stores a computer program, which, when executed by a processor, implements the steps of any of the control methods described in the above embodiments. The computer-readable storage medium may be volatile or non-volatile.

[0131] This invention also provides a computer program product, including computer-readable code, or a non-volatile computer-readable storage medium carrying computer-readable code. When the computer-readable code is run in the processor of an electronic device, the processor in the electronic device executes the above-described control method.

[0132] Those skilled in the art will understand that all or some of the steps, systems, and apparatuses disclosed above, and their functional modules / units, can be implemented as software, firmware, hardware, or suitable combinations thereof. In hardware implementations, the division between functional modules / units mentioned above does not necessarily correspond to the division of physical components; for example, a physical component may have multiple functions, or a function or step may be performed collaboratively by several physical components. Some or all physical components may be implemented as software executed by a processor, such as a central processing unit, digital signal processor, or microprocessor, or as hardware, or as an integrated circuit, such as an application-specific integrated circuit (ASIC). Such software can be distributed on a computer-readable storage medium, which may include computer storage media (or non-transitory media) and communication media (or transient media).

[0133] As is known to those skilled in the art, the term computer storage medium includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information, such as computer-readable program instructions, data structures, program modules, or other data. Computer storage media includes, but is not limited to, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM), static random access memory (SRAM), flash memory or other memory technologies, portable compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical disc storage, magnetic cartridges, magnetic tape, disk storage or other magnetic storage devices, or any other medium that can be used to store desired information and is accessible to a computer. Furthermore, it is known to those skilled in the art that communication media typically contain computer-readable program instructions, data structures, program modules, or other data in modulated data signals such as carrier waves or other transmission mechanisms, and may include any information delivery medium.

[0134] The computer-readable program instructions described herein can be downloaded from computer-readable storage media to various computing / processing devices, or downloaded via a network, such as the Internet, local area network, wide area network, and / or wireless network, to an external computer or external storage device. The network may include copper transmission cables, fiber optic transmission, wireless transmission, routers, firewalls, switches, gateway computers, and / or edge servers. A network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards them to the computer-readable storage media in the respective computing / processing device.

[0135] The computer program instructions used to perform the operations of this invention may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, state setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Smalltalk, C++, etc., and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The computer-readable program instructions may be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or may be connected to an external computer (e.g., via the Internet using an Internet service provider). In some embodiments, electronic circuitry, such as programmable logic circuitry, field-programmable gate arrays (FPGAs), or programmable logic arrays (PLAs), is personalized by utilizing state information from the computer-readable program instructions. This electronic circuitry can execute the computer-readable program instructions to implement various aspects of the invention.

[0136] The computer program product described herein can be implemented specifically through hardware, software, or a combination thereof. In one alternative embodiment, the computer program product is specifically embodied in a computer storage medium; in another alternative embodiment, the computer program product is specifically embodied in a software product, such as a software development kit (SDK), etc.

[0137] Various aspects of the present invention are described herein with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It should be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer-readable program instructions.

[0138] These computer-readable program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus to produce a machine such that, when executed by the processor of the computer or other programmable data processing apparatus, they create means for implementing the functions / actions specified in one or more blocks of the flowchart and / or block diagram. These computer-readable program instructions can also be stored in a computer-readable storage medium that causes a computer, programmable data processing apparatus, and / or other device to operate in a particular manner; thus, the computer-readable medium storing the instructions comprises an article of manufacture that includes instructions for implementing aspects of the functions / actions specified in one or more blocks of the flowchart and / or block diagram.

[0139] Computer-readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device to cause a series of operational steps to be performed on the computer, other programmable data processing apparatus, or other device to produce a computer-implemented process, thereby causing the instructions executed on the computer, other programmable data processing apparatus, or other device to perform the functions / actions specified in one or more boxes of a flowchart and / or block diagram.

[0140] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present invention. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of an instruction, which contains one or more executable instructions for implementing a specified logical function. In some alternative implementations, the functions marked in the blocks may occur in a different order than those shown in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, may be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

[0141] Example embodiments have been disclosed herein, and while specific terminology has been used, it is for illustrative purposes only and should be construed as such, and is not intended to be limiting. In some instances, it will be apparent to those skilled in the art that features, characteristics, and / or elements described in conjunction with particular embodiments may be used alone, or in combination with features, characteristics, and / or elements described in conjunction with other embodiments, unless otherwise expressly indicated. Therefore, those skilled in the art will understand that various changes in form and detail may be made without departing from the scope of the invention as set forth in the appended claims.

Claims

1. A method for output power control based on dynamic wireless charging of electric vehicles, characterized in that, include: Establish a linear parameter time-varying model Gs between the duty cycle and output voltage of the Buck circuit after dynamic wireless charging of electric vehicles, and a model Gd between the input voltage and output voltage of the Buck circuit, and determine the order of the models Gs and Gd. The parameters of the models Gs and Gd are identified based on the auxiliary variable method. Based on the identified models Gs and Gd, a feedback controller Gc and a feedforward controller Gf are designed respectively. The controller is adjusted according to the reference voltage to achieve constant voltage output of the system under dynamic charging.

2. The control method according to claim 1, characterized in that, The standard forms of the linear parameter time-varying models Gs and Gd are: Where x(t) represents the noiseless output of the system, u(t) represents the system input, e(t) represents the system noise, y(t) represents the noisy output of the system, and p t =p( t ) represents the scheduling variable, s represents the differential operator, and H and M represent polynomials in terms of p(t) and s.

3. The control method according to claim 2, characterized in that, The specific expressions for polynomials H and M are: Where n h n m The order of the polynomials in the denominator and numerator of the transfer function, n m <n h , The polynomial representing the denominator coefficients of the transfer function. The polynomial representing the numerator coefficients of the transfer function.

4. The control method according to claim 1, characterized in that, The order of models Gs and Gd is determined by applying a step signal of preset amplitude to the duty cycle of the Buck circuit in the dynamic wireless charging system for electric vehicles and obtaining the system output curve. If the output curve does not oscillate, the system is fitted based on the first-order model. If the output curve oscillates, the system is fitted based on the second-order or higher-order model.

5. The control method according to claim 1, characterized in that, The parameters of models Gs and Gd are identified based on the auxiliary variable method, specifically including: Initial values ​​of the model's parameter vector (0) and the number of iterations λ are set; Noise-free auxiliary variables are generated based on the auxiliary model. , for u(t) k ), y(t) k )and A continuous filter is used for filtering to generate a filtered regression vector. and auxiliary vector , Let y represent the system output and u represent the system input at discrete sampling points t=kTs. Iteratively update the parameter vector according to the parameter update formula. The identification process stops when the number of iterations reaches the upper limit or the parameter vector converges.

6. The control method according to claim 1, characterized in that, The specific method for designing the feedback controller Gc includes: based on the normalized coprime factorization theory, the model Gs is expressed as an H-infinite transfer function with multiplicative uncertainty, weight functions W1 and W2 are selected, and the optimal H-infinite controller Ks is obtained by minimizing the H-infinite cost function. The feedback controller form is Gc = W1KsW2.

7. The control method according to claim 1, characterized in that, The specific method for designing the feedforward controller Gf includes: based on the transfer function from the disturbance to the output, setting the numerator of the transfer function to zero to obtain the expression for the feedforward controller Gf, and dynamically adjusting the gain of Gf according to the output voltage collected by the system in real time.

8. An output power control system based on dynamic wireless charging for electric vehicles, characterized in that, include: The module comprises a model generation module, a model identification module, and a power control module; among which: The model generation module is used to establish a linear parameter time-varying model Gs between the duty cycle and output voltage of the Buck circuit after dynamic wireless charging of electric vehicles, and a model Gd between the input voltage and output voltage of the Buck circuit, and to determine the order of the models Gs and Gd. The model identification module is used to identify the parameters of the models Gs and Gd based on the auxiliary variable method. The power control module is used to design a feedback controller Gc and a feedforward controller Gf based on the identified models Gs and Gd, respectively, and adjust the controllers according to the reference voltage to achieve constant voltage output of the system under dynamic charging.

9. An electronic device, characterized in that, include: One or more processors; Memory, used to store one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement the control method as described in any one of claims 1 to 8.

10. A computer-readable medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method as described in any one of claims 1 to 8.

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