CN115986965A - Load and mutual inductance synchronous identification method for multi-frequency multi-load wireless power transmission system - Google Patents

Load and mutual inductance synchronous identification method for multi-frequency multi-load wireless power transmission system Download PDF

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CN115986965A
CN115986965A CN202310211223.1A CN202310211223A CN115986965A CN 115986965 A CN115986965 A CN 115986965A CN 202310211223 A CN202310211223 A CN 202310211223A CN 115986965 A CN115986965 A CN 115986965A
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load
frequency
mutual inductance
fitness
value
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汪凤翔
黄东晓
魏钦旺
陈军希
于新红
柯栋梁
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Quanzhou Institute of Equipment Manufacturing
Mindu Innovation Laboratory
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Mindu Innovation Laboratory
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    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
    • Y02T10/00—Road transport of goods or passengers
    • Y02T10/60—Other road transportation technologies with climate change mitigation effect
    • Y02T10/70—Energy storage systems for electromobility, e.g. batteries
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
    • Y02T10/00—Road transport of goods or passengers
    • Y02T10/60—Other road transportation technologies with climate change mitigation effect
    • Y02T10/7072—Electromobility specific charging systems or methods for batteries, ultracapacitors, supercapacitors or double-layer capacitors

Abstract

The invention relates to a method for synchronously identifying loads and mutual inductance of a multi-frequency multi-load wireless power transmission system, which comprises the steps of firstly establishing a system input impedance equation set under different frequencies under a system steady state to obtain a relational expression of the mutual inductance and the loads; meanwhile, the frequency division extraction of the primary multi-frequency superposed current is carried out according to the working frequency component of the system by adopting a sliding window DFT; and then designing a particle swarm optimization algorithm by taking the error between the actual value and the theoretical value of the output voltage as a fitness function, converting the parameter identification problem into an algorithm optimization problem, and carrying out optimal solution search on the parameter to be identified to replace the traditional calculation method, thereby avoiding the error generated by the traditional equation. The invention only needs to carry out model analysis on the system input impedance, has simple circuit structure, does not need additional control circuit, and only needs to sample the input bus voltage, the primary side current and the output voltage, can effectively reduce the communication data volume, simultaneously reduces the circuit complexity, reduces the system volume and expands the working range of the wireless charging system.

Description

Load and mutual inductance synchronous identification method for multi-frequency multi-load wireless power transmission system
Technical Field
The invention belongs to the technical field of wireless charging, and particularly relates to a load and mutual inductance identification method of a multi-frequency multi-load wireless electric energy system.
Background
In recent years, wireless Power Transfer (WPT) is gradually used in medium-low power electronic devices, and magnetic coupling resonant wireless power transfer (MCR-WPT) has become one of the main development directions of wireless power transmission due to advantages such as long transmission distance, high transmission power, and high safety. In the development process of wireless power transmission, a multi-load system has received wide attention because it has industrial significance.
Whether single or multiple loads, the most likely changes in the use of a wireless charging system are the relative position of the resonators and the impedance of the attached devices. The transmission performance of the system is reduced or even out of control due to the deviation of the resonator, the equivalent impedance change of the load and the like. In order to ensure that the system can realize efficient transmission performance and correct the system model in real time, a method capable of accurately identifying mutual inductance and load needs to be designed so as to improve the accuracy of the model.
At present, there is a method for identifying load and mutual inductance of a multi-load wireless power transmission system based on a time division multiplexing method, which converts a multi-load system into a single-load system working in different time sequences, and realizes the division of the working time sequences of the multi-load; the identification process needs to collect the voltage and current of the power bus and the DC output voltage of the system. The method essentially belongs to parameter identification of a single-load wireless charging system, and cannot be applied to an application scene of multi-load wireless charging; meanwhile, an extra circuit is needed to adjust the bus voltage in the identification process, so that the overshoot phenomenon is prevented, the control difficulty is high, and the realization is difficult.
Therefore, how to provide a method for synchronously identifying the load and mutual inductance of a multi-frequency multi-load wireless power transmission system to realize real-time identification of multiple parameters of the multi-load wireless charging system, thereby expanding the working range of the wireless charging system and becoming a problem to be solved urgently.
Disclosure of Invention
The invention aims to provide a method for synchronously identifying load and mutual inductance of a multi-frequency multi-load wireless power transmission system, which can realize real-time identification of the load and the mutual inductance of the multi-load wireless charging system and further expand the working range of the wireless charging system.
The invention discloses a method for synchronously identifying loads and mutual inductance of a multi-frequency multi-load wireless power transmission system, which is applied to a multi-load magnetic coupling resonance system and comprises the following steps:
step 10, obtaining a multi-frequency driving signal through a sinusoidal pulse width modulation mode of superposing modulation waves with different frequencies and comparing carrier waves, injecting energy with various different frequencies into a multi-load wireless charging system based on a multi-frequency resonance compensation network, and transmitting power to a plurality of loads through the multi-frequency resonance compensation network by a transmitting end;
step 20, modeling input impedance of the system under different frequencies to obtain a relational expression between the load and mutual inductance;
step 30, extracting primary multi-frequency superposed current according to system working frequency component frequency division by adopting a sliding window DFT, sampling system input bus voltage, primary current and direct current output voltage in real time, calculating through data obtained by sampling and charging parameters of a system to obtain an identification model output voltage calculated value, and then taking the error between an actual system output voltage value and the identification model output voltage calculated value as a target function for evaluating the fitness of particles;
and step 40, optimizing the target function by using a particle swarm algorithm, taking a global optimal solution searched when the particle swarm algorithm is finished as a load value, and then determining a mutual inductance value according to a relational expression of mutual inductance and the load, so that the load and the mutual inductance of the multi-load wireless charging system are synchronously identified in real time.
The method comprises the following steps of:
step 21, performing Fourier series expansion on the inverted output voltage, and taking the fundamental wave of the output voltage
Figure BDA0004112760980000021
Wherein i =1,2,. N,. Is @>
Figure BDA0004112760980000022
For inverting the output voltage component of different frequencies, a i As a modulation ratio, E dc Is a dc bus voltage; i represents any modulation ratio, any working frequency and a receiving end loop or load, and n represents the number of the parallel LC networks;
step 22, the equivalent impedance of the transmitting end multi-resonant frequency compensation network is as follows:
Figure BDA0004112760980000023
where ω is the angular frequency of system operation, L pn To compensate the inductance at the primary side, C pn A primary side compensation capacitor;
the relational expression between the load and the mutual inductance takes a double-frequency double-load MCR-WPT system as an example, and the system working under different frequencies has the following input impedance equation set:
Figure BDA0004112760980000031
in the formula, R 1 ＝R eq1 +R s1 、R 2 ＝R eq2 +R s2 、μ＝ω 1 L s2 -1/(ω 1 C s2 )、β＝ω 2 L s1 -1/(ω 2 C s1 ),
Figure BDA0004112760980000032
And &>
Figure BDA0004112760980000033
Is an input impedance at different frequencies, L s1 And L s2 Compensating inductance, C, for secondary side s1 And C s2 For secondary side compensation of capacitance, R p Is the primary side coil internal resistance, R s1 And R s2 Is the secondary side coil internal resistance, R L1 And R L2 Is a secondary side load, M ps1 And M ps2 For mutual inductance of coils, omega 1 And omega 2 The system operating angular frequency;
according to an input impedance equation set of the system working at different frequencies, a relational expression between the load and the mutual inductance can be obtained:
Figure BDA0004112760980000034
in the formula (I), the compound is shown in the specification,
Figure BDA0004112760980000035
the step 30 comprises:
step 31, the fundamental current expression extracted by the sliding window DFT is:
Figure BDA0004112760980000036
/>
wherein, I p (N) is the signal value at N moments, N is the number of sampling points in one period, A 1 And B 1 Are the real and imaginary coefficients of the current expression, i.e.:
Figure BDA0004112760980000037
in the formula, N cur For the current sampling point, N cur -N +1 is the initial sampling point;
step 32, the calculated value of the output voltage of the identification model is as follows:
Figure BDA0004112760980000041
wherein, C fi Is a post-stage filter capacitor on the rectification side, P i For system output power, T is run time, V i Outputting a voltage for the ith load; r Li Represents the ith load; k represents the kth time of T;
step 33, outputting the actual system output voltage value V i * And identifying model output voltage calculation value V i As an objective function for evaluating the fitness of the particle:
Figure BDA0004112760980000042
the step 40 includes:
step 41, setting an iteration threshold, and inputting a mutual inductance value between a transmitting end and a receiving end as particles into a particle swarm algorithm;
step 42, initializing the speed and position of each particle;
step 43, calculating an inertia weight factor of each particle;
step 44, updating the speed and the position of each particle based on the inertia weight factor;
step 45, calculating the fitness of each particle based on the objective function, and determining the individual optimal value and the global optimal value of each particle based on the fitness;
step 46, outputting a global optimal value based on the iteration threshold and the fitness, and taking a global optimal solution as a load value;
and step 47, simultaneously obtaining the size of the mutual inductance and the load according to a relational expression between the load and the mutual inductance.
The step 45 comprises:
step 451, calculating the fitness (n) of the nth iteration of each particle based on the objective function;
step 452, determining whether the fitness (n) is less than the fitness (n-1), if so, making the individual optimal value gbest (n) = fitness (n), and going to step 453; if not, go to step 453;
step 453, determine whether the fitness (n) is less than the global optimum zbest (n), if so, let the global optimum zbest (n) = fitness (n), and go to step 454; if not, go to step 454;
step 454, after the iteration number n is added by 1, the process proceeds to step 46.
By adopting the technical scheme of the invention, firstly, a system input impedance equation set under different frequencies is established under the system steady state, and a mutual inductance-related load relational expression is obtained by solving; meanwhile, frequency division extraction is carried out on the primary multi-frequency superposed current by adopting a sliding window DFT; and then designing a particle swarm optimization algorithm by taking the error between the actual value and the theoretical value of the output voltage as a fitness function, converting the parameter identification problem into an algorithm optimization problem, and carrying out optimal solution search on the parameter to be identified to replace the traditional calculation method, thereby avoiding the error generated by the traditional equation. The invention only needs to carry out model analysis on the input impedance of the system, has simple circuit structure, does not need additional control circuits, and only needs to sample the input bus voltage, the primary side current and the output voltage, can effectively reduce the communication data volume, simultaneously reduces the circuit complexity, reduces the system volume and expands the working range of the wireless charging system.
Drawings
Fig. 1 (a) is a main circuit diagram of a multi-load wireless charging system according to the present invention;
fig. 1 (b) is a primary circuit diagram of a multi-frequency compensation network-based multi-load wireless charging system according to the present invention;
FIG. 2 is a general block diagram of a multi-load wireless charging system according to the present invention;
FIG. 3 is a flow chart of mutual inductance and load synchronous identification in the present invention;
FIG. 4 is a flow chart of the sliding window DFT current detection in the present invention.
The invention is described in further detail below with reference to the figures and specific examples.
Detailed Description
The embodiment of the application provides a load and mutual inductance synchronous identification method for a multi-frequency multi-load wireless power transmission system, so that the load and mutual inductance of the multi-load wireless charging system can be identified in real time, and the working range of the wireless charging system is further expanded.
The multi-load wireless charging system based on the multi-frequency resonance compensation network in the embodiment of the application is a wireless electric energy transmission system which is designed at a transmitting end circuit and is provided with the multi-frequency resonance compensation network to realize multi-frequency energy, and the general idea of the technical scheme is as follows: firstly, establishing a system input impedance equation set under different frequencies in a system steady state, and solving to obtain a relational expression of mutual inductance and load; meanwhile, frequency division extraction is carried out on the primary multi-frequency superposed current by adopting a sliding window DFT; and then designing a particle swarm optimization algorithm by taking the error between the actual value and the theoretical value of the output voltage as a fitness function, converting the parameter identification problem into an algorithm optimization problem, and carrying out optimal solution search on the parameter to be identified to replace the traditional calculation method, thereby avoiding the error generated by the traditional equation. The method only needs to analyze the input impedance model of the system, and has simple circuit structure without an additional control circuit. According to the method, only the input bus voltage, the primary side current and the output voltage need to be sampled, the communication data volume is reduced, the circuit complexity is reduced, the system size is reduced, and the working range of the wireless charging system is expanded.
In the embodiment of the present invention, the multi-load wireless charging system based on the multi-frequency resonance compensation network, as shown in fig. 1 (a) and (b), includes a regulated dc power supply at the transmitting end, and a full-bridge inverter (S) 1 ～S 4 ) The device comprises a resonator, a rectifying and filtering module at a receiving end and a load; the voltage-stabilizing direct-current power supply outputs high-frequency alternating current through the conversion of a full-bridge inverter, then transmits energy to a plurality of receiving ends through a magnetic field by a resonator, and finally carries out rectification filtering by a rectification filtering module and transmits the energy to a load; the full-bridge inverter consists of GaN-MOSFET; the resonanceThe device consists of a symmetrical circular coil wound by litz wires and comprises a transmitting end resonance circuit and a receiving end resonance circuit; the transmitting end of the multi-load wireless charging system converts a direct-current power supply by using a full-bridge inverter to generate high-frequency alternating-current voltage; the rectification filtering module at the receiving end uses an uncontrollable bridge rectifier to simplify the control difficulty; the resonator consists of n-1 parallel LC networks and series inductors and capacitors.
(1) The transmission end resonant circuit adopts a multi-frequency resonance compensation network topology design
The transmitting end resonance circuit of the invention adopts a multi-frequency resonance compensation network which can independently control the input phase under n resonance frequencies, as shown in fig. 1 (b), the multi-frequency resonance compensation network consists of a capacitor and n-1 parallel LC circuits, when the multi-load wireless charging system works in a resonance state, the phase angle of the system input impedance under the corresponding resonance frequency is zero, and the multi-frequency reactive component can be completely eliminated.
(2) Sliding window DFT design
As shown in fig. 4, the present invention detects each frequency component current signal in the primary side circuit by the sliding window DFT current detection method, and only iterative computation is needed for the current sampling point, and iterative computation is not needed for the sampling points in the whole period, thereby reducing the computation amount and computation time.
(3) Identification module design
In order to realize multi-parameter identification of the multi-frequency multi-load wireless charging system, the invention provides a method for establishing a mutual inductance and load relational expression by using system input impedance under different frequencies, designing a particle swarm algorithm by using an actual value and a theoretical value error of output voltage as a fitness function, using a global optimal solution searched when the operation of the particle swarm algorithm is finished as a load value, and then determining a mutual inductance value according to the relational expression of the mutual inductance and the load. The identification process is shown in FIG. 3.
As shown in fig. 2 to 4, the method for synchronously identifying the load and the mutual inductance of the multi-frequency multi-load wireless power transmission system of the present invention is applied to a multi-load magnetic coupling resonance system, and comprises the following steps:
step 10, obtaining a multi-frequency driving signal by a sinusoidal pulse width modulation mode of comparing superposed different-frequency modulation waves with carriers, injecting multiple kinds of energy with different frequencies into a multi-load wireless charging system based on a multi-frequency resonance compensation network, and transmitting power to multiple loads by a transmitting end through the multi-frequency resonance compensation network;
step 20, modeling input impedance of the system under different frequencies to obtain a relational expression between the load and mutual inductance;
step 30, extracting primary multi-frequency superposed current according to system working frequency component frequency division by adopting a sliding window DFT, sampling system input bus voltage, primary current and direct current output voltage in real time, calculating through data obtained by sampling and charging parameters of a system to obtain an identification model output voltage calculated value, and then taking the error between an actual system output voltage value and the identification model output voltage calculated value as a target function for evaluating the fitness of particles;
and step 40, optimizing the target function by using a particle swarm algorithm, taking a global optimal solution searched when the particle swarm algorithm is finished as a load value, and then determining a mutual inductance value according to a relational expression of mutual inductance and the load, so that the load and the mutual inductance of the multi-load wireless charging system are synchronously identified in real time.
The step 20 comprises:
step 21, performing Fourier series expansion on the inverted output voltage, and taking the fundamental wave of the inverted output voltage
Figure BDA0004112760980000071
Wherein i =1,2,. N,. Is @>
Figure BDA0004112760980000072
For inverting the output voltage component of different frequencies, a i As a modulation ratio, E dc Is a dc bus voltage; i represents any modulation ratio, any working frequency and a receiving end loop or load, and n represents the number of the parallel LC networks;
step 22, the equivalent impedance of the transmitting end multi-resonant frequency compensation network is as follows:
Figure BDA0004112760980000073
where ω is the angular frequency of system operation, L pn To compensate the inductance for the primary side, C pn A primary side compensation capacitor;
the relational expression between the load and the mutual inductance takes a double-frequency double-load MCR-WPT system as an example, and the system working under different frequencies has the following input impedance equation set:
Figure BDA0004112760980000074
in the formula, R 1 ＝R eq1 +R s1 、R 2 ＝R eq2 +R s2 、μ＝ω 1 L s2 -1/(ω 1 C s2 )、β＝ω 2 L s1 -1/(ω 2 C s1 )。
Figure BDA0004112760980000075
And &>
Figure BDA0004112760980000076
Is an input impedance at different frequencies, L s1 And L s2 Compensating inductance, C, for secondary side s1 And C s2 For secondary side compensation of capacitance, R p Is the primary side coil internal resistance, R s1 And R s2 Is the secondary side coil internal resistance, R L1 And R L2 As a secondary side load, M ps1 And M ps2 Is coil mutual inductance, omega 1 And ω 2 The system operating angular frequency;
according to the input impedance equation system of the system working under different frequencies, a relational expression between the load and the mutual inductance can be obtained:
Figure BDA0004112760980000081
in the formula (I), the compound is shown in the specification,
Figure BDA0004112760980000082
the step 30 comprises:
step 31, the fundamental current expression extracted by the sliding window DFT is:
Figure BDA0004112760980000083
wherein, I p (N) is the signal value at N moments, N is the number of sampling points in one period, A 1 And B 1 Are the real and imaginary coefficients of the current expression, i.e.:
Figure BDA0004112760980000084
in the formula, N cur For the current sampling point, N cur -N +1 is the initial sampling point;
step 32, the calculated value of the output voltage of the identification model is as follows:
Figure BDA0004112760980000085
wherein, C fi For a post-stage filter capacitor on the rectifier side, P i For system output power, T is run time, V i Outputting a voltage for the ith load; r Li Represents the ith load; k represents the kth time of T;
step 33, outputting the actual system output voltage value V i * And identifying model output voltage calculation value V i As an objective function for evaluating the fitness of the particle:
Figure BDA0004112760980000091
the step 40 comprises:
step 41, setting an iteration threshold, and inputting a mutual inductance value between a transmitting end and a receiving end as particles into a particle swarm algorithm;
step 42, initializing the speed and position of each particle;
step 43, calculating an inertia weight factor of each particle;
step 44, updating the speed and the position of each particle based on the inertia weight factor;
step 45, calculating the fitness of each particle based on the objective function, and determining the individual optimal value and the global optimal value of each particle based on the fitness;
step 46, outputting a global optimal value based on the iteration threshold and the fitness, and taking a global optimal solution as a load value;
and step 47, obtaining the mutual inductance and the load size at the same time according to the relational expression between the load and the mutual inductance.
The step 45 comprises:
step 451, calculating the fitness (n) of the nth iteration of each particle based on the objective function;
step 452, determining whether the fitness (n) is less than the fitness (n-1), if so, making the individual optimal value gbest (n) = fitness (n), and going to step 453; if not, go to step 453;
step 453, determine whether the fitness (n) is less than the global optimum zbest (n), if so, let the global optimum zbest (n) = fitness (n), and go to step 454; if not, go to step 454;
step 454, after the iteration number n is added by 1, the process proceeds to step 46.
The technical key points of the invention are as follows:
the directional transmission of the power of the multi-load wireless power transmission system is realized by adding a multi-resonant frequency compensation network on the primary side, no additional control circuit is needed, the cross coupling influence between receiving ends is small and can be ignored;
aiming at the situation that multi-frequency superposed current exists in a primary side circuit, a current signal corresponding to a working frequency needs to be sampled in the identification process, and therefore a sliding window DFT current detection method is adopted to extract fundamental wave components of corresponding frequencies of the primary side current signal;
the method comprises the steps of obtaining a mutual inductance and load relational expression by establishing input impedance calculation of a system working under different frequencies, introducing a particle swarm algorithm, creating a fitness function by sampling a difference value of output voltage and predicted output voltage, converting a parameter identification problem into an algorithm optimization problem, and performing optimal solution search on identification parameters to replace a traditional calculation method, so that errors generated by a traditional equation are avoided;
by sampling the power bus voltage, the primary side current and the direct current output voltage of the wireless charging system in real time, high-frequency large voltages at two ends of a device in the coupling mechanism do not need to be measured directly, and the wireless charging system is safer, low in algorithm complexity, short in operation time and small in error.
After the technical scheme of the invention is adopted, when mutual inductance is disturbed and deviates from a set value, the magnitude between the mutual inductance and the load can be effectively identified and the value of the mutual inductance and the load in a prediction model is corrected; the dynamic stability and the quick response capability of the wireless charging system can be ensured by the joint work of a model predictive control algorithm (MPC algorithm) and a particle swarm optimization (PSO algorithm); the invention can be used under dynamic or static conditions by combining the PSO algorithm and the MPC algorithm, so that the wireless charging is more reliable; the method and the device can realize the estimation of the imaginary part of the receiving end in an off-line state and can also realize the estimation of the imaginary part of the receiving end of a dynamic wireless charging system, thereby greatly improving the practicability of the method and the device.
Although specific embodiments of the invention have been described above, it will be understood by those skilled in the art that the specific embodiments described are illustrative only and are not limiting upon the scope of the invention, and that equivalent modifications and variations can be made by those skilled in the art without departing from the spirit of the invention, which is to be limited only by the appended claims.

Claims (2)

1. A method for synchronously identifying loads and mutual inductance of a multi-frequency multi-load wireless power transmission system is applied to a multi-load magnetic coupling resonance system and is characterized by comprising the following steps:
step 10, obtaining a multi-frequency driving signal through a sinusoidal pulse width modulation mode of superposing modulation waves with different frequencies and comparing carrier waves, injecting energy with various different frequencies into a multi-load wireless charging system based on a multi-frequency resonance compensation network, and transmitting power to a plurality of loads through the multi-frequency resonance compensation network by a transmitting end;
step 20, modeling input impedance of the system under different frequencies to obtain a relational expression between the load and mutual inductance;
step 30, extracting the primary multi-frequency superposed current by adopting a sliding window DFT according to the frequency division of the system working frequency component, sampling the system input bus voltage, the primary current and the direct current output voltage in real time, calculating through the sampled data and the charging parameters of the system to obtain an identification model output voltage calculation value, and then taking the error between the actual system output voltage value and the identification model output voltage calculation value as a target function for evaluating the fitness of the particles;
and step 40, optimizing the target function by using a particle swarm algorithm, taking a global optimal solution searched when the particle swarm algorithm is finished as a load value, and then determining a mutual inductance value according to a relational expression of mutual inductance and the load, so that the load and the mutual inductance of the multi-load wireless charging system are synchronously identified in real time.
2. The method of claim 1, wherein the method for synchronously identifying the load and the mutual inductance of the multi-frequency multi-load wireless power transmission system comprises the following steps:
the method comprises the following steps of:
step 21, performing Fourier series expansion on the inverted output voltage, and taking the fundamental wave of the output voltage
Figure FDA0004112760970000011
Wherein i =1,2,. N,. Is @>
Figure FDA0004112760970000012
For different frequency inversion outputVoltage component a i As a modulation ratio, E dc Is the DC bus voltage; i represents any modulation ratio, any working frequency and a receiving end loop or load, and n represents the number of the parallel LC networks;
step 22, the equivalent impedance of the transmitting end multi-resonant frequency compensation network is as follows:
Figure FDA0004112760970000013
where ω is the angular frequency of system operation, L pn To compensate the inductance at the primary side, C pn A compensation capacitor for the primary side;
the relational expression between the load and the mutual inductance takes a double-frequency double-load MCR-WPT system as an example, and the system working at different frequencies is set as follows:
Figure FDA0004112760970000021
in the formula, R 1 ＝R eq1 +R s1 、R 2 ＝R eq2 +R s2 、μ＝ω 1 L s2 -1/(ω 1 C s2 )、β＝ω 2 L s1 -1/(ω 2 C s1 )，
Figure FDA0004112760970000022
And &>
Figure FDA0004112760970000023
Is an input impedance at different frequencies, L s1 And L s2 Compensating inductance, C, for secondary side s1 And C s2 For secondary side compensation of capacitance, R p Is the primary side coil internal resistance, R s1 And R s2 Is the secondary side coil internal resistance, R L1 And R L2 Is a secondary side load, M ps1 And M ps2 For mutual inductance of coils, omega 1 And ω 2 The system operating angular frequency;
according to an input impedance equation set of the system working at different frequencies, a relational expression between the load and the mutual inductance can be obtained:
Figure FDA0004112760970000024
in the formula (I), the compound is shown in the specification,
Figure FDA0004112760970000025
the step 30 comprises:
step 31, the fundamental current expression extracted by the sliding window DFT is:
Figure FDA0004112760970000026
wherein, I p (N) is the signal value at N times, N is the number of sampling points in one period, A 1 And B 1 Are the real and imaginary coefficients of the current expression, i.e.:
Figure FDA0004112760970000027
in the formula, N cur For the current sampling point, N cur -N +1 is the initial sampling point;
step 32, the calculated value of the output voltage of the identification model is as follows:
Figure FDA0004112760970000031
wherein, C fi For a post-stage filter capacitor on the rectifier side, P i For system output power, T is run time, V i Outputting a voltage for the ith load; r Li Represents the ith load; k represents the kth time of T;
step 33, outputting the actual system output voltage value V i * And identifying model output voltage calculation value V i As an objective function for evaluating the fitness of the particle:
Figure FDA0004112760970000032
the step 40 includes:
step 41, setting an iteration threshold, and inputting a mutual inductance value between a transmitting end and a receiving end as particles into a particle swarm algorithm;
step 42, initializing the speed and position of each particle;
step 43, calculating an inertia weight factor of each particle;
step 44, updating the speed and the position of each particle based on the inertia weight factor;
step 45, calculating the fitness of each particle based on the objective function, and determining the individual optimal value and the global optimal value of each particle based on the fitness;
step 46, outputting a global optimal value based on the iteration threshold and the fitness, and taking a global optimal solution as a load value;
and step 47, obtaining the mutual inductance and the load size at the same time according to the relational expression between the load and the mutual inductance.
The step 45 comprises:
step 451, calculating the fitness (n) of the nth iteration of each particle based on the objective function;
step 452, determining whether the fitness (n) is less than the fitness (n-1), if so, making the individual optimal value gbest (n) = fitness (n), and going to step 453; if not, go to step 453;
step 453, determine whether the fitness (n) is less than the global optimum zbest (n), if so, let the global optimum zbest (n) = fitness (n), and go to step 454; if not, go to step 454;
step 454, after the iteration number n is added by 1, the process proceeds to step 46.
CN202310211223.1A 2023-03-07 2023-03-07 Load and mutual inductance synchronous identification method for multi-frequency multi-load wireless power transmission system Pending CN115986965A (en)

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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117060604A (en) * 2023-10-12 2023-11-14 南方电网数字电网研究院有限公司 Wireless power supply system and power transmission system
CN117060604B (en) * 2023-10-12 2024-03-12 南方电网数字电网研究院股份有限公司 Wireless power supply system and power transmission system

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