CN117081276A - Efficacy improving method of double-parameter disturbance wireless power transmission system based on Q-learning algorithm - Google Patents

Efficacy improving method of double-parameter disturbance wireless power transmission system based on Q-learning algorithm Download PDF

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CN117081276A
CN117081276A CN202310958668.6A CN202310958668A CN117081276A CN 117081276 A CN117081276 A CN 117081276A CN 202310958668 A CN202310958668 A CN 202310958668A CN 117081276 A CN117081276 A CN 117081276A
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China
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wireless power
power transmission
value
compensation
magnetic coupling
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刘旭
晁洁
鲁大民
施羽彤
夏晨阳
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China University of Mining and Technology CUMT
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China University of Mining and Technology CUMT
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    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J50/00—Circuit arrangements or systems for wireless supply or distribution of electric power
    • H02J50/70—Circuit arrangements or systems for wireless supply or distribution of electric power involving the reduction of electric, magnetic or electromagnetic leakage fields
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L53/00—Methods of charging batteries, specially adapted for electric vehicles; Charging stations or on-board charging equipment therefor; Exchange of energy storage elements in electric vehicles
    • B60L53/10—Methods of charging batteries, specially adapted for electric vehicles; Charging stations or on-board charging equipment therefor; Exchange of energy storage elements in electric vehicles characterised by the energy transfer between the charging station and the vehicle
    • B60L53/12—Inductive energy transfer
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L53/00—Methods of charging batteries, specially adapted for electric vehicles; Charging stations or on-board charging equipment therefor; Exchange of energy storage elements in electric vehicles
    • B60L53/10—Methods of charging batteries, specially adapted for electric vehicles; Charging stations or on-board charging equipment therefor; Exchange of energy storage elements in electric vehicles characterised by the energy transfer between the charging station and the vehicle
    • B60L53/12—Inductive energy transfer
    • B60L53/122—Circuits or methods for driving the primary coil, e.g. supplying electric power to the coil
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N20/00—Machine learning
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J50/00—Circuit arrangements or systems for wireless supply or distribution of electric power
    • H02J50/10—Circuit arrangements or systems for wireless supply or distribution of electric power using inductive coupling
    • H02J50/12—Circuit arrangements or systems for wireless supply or distribution of electric power using inductive coupling of the resonant type
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J50/00—Circuit arrangements or systems for wireless supply or distribution of electric power
    • H02J50/80—Circuit arrangements or systems for wireless supply or distribution of electric power involving the exchange of data, concerning supply or distribution of electric power, between transmitting devices and receiving devices
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J7/00—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries
    • H02J7/00032—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries characterised by data exchange
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J7/00—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries
    • H02J7/02—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries for charging batteries from ac mains by converters
    • H02J7/04—Regulation of charging current or voltage
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02M—APPARATUS FOR CONVERSION BETWEEN AC AND AC, BETWEEN AC AND DC, OR BETWEEN DC AND DC, AND FOR USE WITH MAINS OR SIMILAR POWER SUPPLY SYSTEMS; CONVERSION OF DC OR AC INPUT POWER INTO SURGE OUTPUT POWER; CONTROL OR REGULATION THEREOF
    • H02M3/00—Conversion of dc power input into dc power output
    • H02M3/01—Resonant DC/DC converters
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02M—APPARATUS FOR CONVERSION BETWEEN AC AND AC, BETWEEN AC AND DC, OR BETWEEN DC AND DC, AND FOR USE WITH MAINS OR SIMILAR POWER SUPPLY SYSTEMS; CONVERSION OF DC OR AC INPUT POWER INTO SURGE OUTPUT POWER; CONTROL OR REGULATION THEREOF
    • H02M3/00—Conversion of dc power input into dc power output
    • H02M3/22—Conversion of dc power input into dc power output with intermediate conversion into ac
    • H02M3/24—Conversion of dc power input into dc power output with intermediate conversion into ac by static converters
    • H02M3/28—Conversion of dc power input into dc power output with intermediate conversion into ac by static converters using discharge tubes with control electrode or semiconductor devices with control electrode to produce the intermediate ac
    • H02M3/325—Conversion of dc power input into dc power output with intermediate conversion into ac by static converters using discharge tubes with control electrode or semiconductor devices with control electrode to produce the intermediate ac using devices of a triode or a transistor type requiring continuous application of a control signal
    • H02M3/335—Conversion of dc power input into dc power output with intermediate conversion into ac by static converters using discharge tubes with control electrode or semiconductor devices with control electrode to produce the intermediate ac using devices of a triode or a transistor type requiring continuous application of a control signal using semiconductor devices only
    • H02M3/33569—Conversion of dc power input into dc power output with intermediate conversion into ac by static converters using discharge tubes with control electrode or semiconductor devices with control electrode to produce the intermediate ac using devices of a triode or a transistor type requiring continuous application of a control signal using semiconductor devices only having several active switching elements
    • H02M3/33573—Full-bridge at primary side of an isolation transformer
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02M—APPARATUS FOR CONVERSION BETWEEN AC AND AC, BETWEEN AC AND DC, OR BETWEEN DC AND DC, AND FOR USE WITH MAINS OR SIMILAR POWER SUPPLY SYSTEMS; CONVERSION OF DC OR AC INPUT POWER INTO SURGE OUTPUT POWER; CONTROL OR REGULATION THEREOF
    • H02M7/00—Conversion of ac power input into dc power output; Conversion of dc power input into ac power output
    • H02M7/02—Conversion of ac power input into dc power output without possibility of reversal
    • H02M7/04—Conversion of ac power input into dc power output without possibility of reversal by static converters
    • H02M7/06—Conversion of ac power input into dc power output without possibility of reversal by static converters using discharge tubes without control electrode or semiconductor devices without control electrode
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02M—APPARATUS FOR CONVERSION BETWEEN AC AND AC, BETWEEN AC AND DC, OR BETWEEN DC AND DC, AND FOR USE WITH MAINS OR SIMILAR POWER SUPPLY SYSTEMS; CONVERSION OF DC OR AC INPUT POWER INTO SURGE OUTPUT POWER; CONTROL OR REGULATION THEREOF
    • H02M7/00—Conversion of ac power input into dc power output; Conversion of dc power input into ac power output
    • H02M7/42—Conversion of dc power input into ac power output without possibility of reversal
    • H02M7/44—Conversion of dc power input into ac power output without possibility of reversal by static converters
    • H02M7/48—Conversion of dc power input into ac power output without possibility of reversal by static converters using discharge tubes with control electrode or semiconductor devices with control electrode
    • H02M7/53—Conversion of dc power input into ac power output without possibility of reversal by static converters using discharge tubes with control electrode or semiconductor devices with control electrode using devices of a triode or transistor type requiring continuous application of a control signal
    • H02M7/537—Conversion of dc power input into ac power output without possibility of reversal by static converters using discharge tubes with control electrode or semiconductor devices with control electrode using devices of a triode or transistor type requiring continuous application of a control signal using semiconductor devices only, e.g. single switched pulse inverters
    • H02M7/5387—Conversion of dc power input into ac power output without possibility of reversal by static converters using discharge tubes with control electrode or semiconductor devices with control electrode using devices of a triode or transistor type requiring continuous application of a control signal using semiconductor devices only, e.g. single switched pulse inverters in a bridge configuration
    • H02M7/53871—Conversion of dc power input into ac power output without possibility of reversal by static converters using discharge tubes with control electrode or semiconductor devices with control electrode using devices of a triode or transistor type requiring continuous application of a control signal using semiconductor devices only, e.g. single switched pulse inverters in a bridge configuration with automatic control of output voltage or current
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2207/00—Indexing scheme relating to details of circuit arrangements for charging or depolarising batteries or for supplying loads from batteries
    • H02J2207/20—Charging or discharging characterised by the power electronics converter

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Abstract

The application relates to a dual-parameter disturbance wireless power transmission system efficacy improving method based on a Q-learning algorithm. The method comprises the following steps: constructing a circuit topology structure of a magnetic coupling wireless power transmission system with a resonant network being LCC-LCC, and further constructing the magnetic coupling wireless power transmission system; and acquiring a three-dimensional Q table corresponding to the output system power and transmission efficiency under the given variation range of the mutual inductance and the system load to form a data set, defining a state space, an action space, an initial state, a reward function and a related state space and action space of the system, training a controller of the primary compensation topology and the switch compensation capacitor of the transmitting coil module by adopting a reinforcement learning Q-learning algorithm model, and outputting the trained three-dimensional Q table to obtain the optimal capacitance value of the switch compensation capacitor of the system when the resistance values of the mutual inductance and the system load are changed, so that the controller adjusts the switch compensation capacitor to the optimal capacitance value. And the transmission performance of the system is improved.

Description

Efficacy improving method of double-parameter disturbance wireless power transmission system based on Q-learning algorithm
Technical Field
The application relates to the technical field of wireless power transmission, in particular to a method for improving the efficacy of a double-parameter disturbance wireless power transmission system based on a Q-learning algorithm.
Background
The wireless power transmission (Wireless Power Transfer, WPT) technology has the advantages of convenience, rapidness, flexibility, safety and the like, and is widely applied to the fields of electric automobiles, intelligent home furnishings, medical equipment and the like. In order to ensure an efficient energy transfer, the primary circuit is required to generate a frequency-stable high-frequency sinusoidal current in the transmitting coil via an inverter and a resonant network. However, when the WPT system works in various environments, there are many factors that may cause the change of circuit parameters, for example, the load of the actual WPT system is often a battery, and the equivalent resistance value in the external characteristic of the battery changes with the electric quantity of the battery; for example, in the charging process, the relative positions of the transmitting coil and the receiving coil are offset to cause the mutual inductance of the system to change, which can affect the transmission power and the transmission efficiency of the electric automobile, so that the WPT system deviates from the maximum efficiency point or the maximum power point, and the transmission performance of the system is reduced.
Disclosure of Invention
Based on the foregoing, it is necessary to provide a method for improving the efficiency of a dual-parameter disturbance wireless power transmission system based on a Q-learning algorithm, which can improve the transmission performance of the system.
A method for improving the efficiency of a dual-parameter disturbance wireless power transmission system based on a Q-learning algorithm is characterized by comprising the following steps:
constructing a resonant network as a circuit topology structure of a magnetic coupling wireless power transmission system of LCC-LCC, wherein the magnetic coupling wireless power transmission system comprises a direct current power supply, a high-frequency inversion module, a primary side compensation topology and transmitting coil module, a receiving coil and secondary side compensation topology module, a rectifying and filtering module and a system load which are sequentially connected;
constructing a magnetic coupling wireless power transmission system according to the circuit topology structure of the magnetic coupling wireless power transmission system;
acquiring system power and transmission efficiency which are correspondingly output by the magnetic coupling wireless power transmission system under the conditions of a given mutual inductance change range, a given resistance change range of a system load and a given switch compensation capacitance change range, and forming a data set;
defining a three-dimensional Q table of a state space, an action space, an initial state, a reward function and an associated state space and action space of the magnetic coupling wireless power transmission system according to the data set;
based on a state space, an action space, an initial state, a reward function and a three-dimensional Q table of the magnetic coupling wireless power transmission system, performing iterative training on the primary side compensation topology and a controller of a switch compensation capacitor of a transmitting coil module by adopting a reinforcement learning Q-learning algorithm model until the reinforcement learning Q-learning algorithm model converges, and outputting a trained three-dimensional Q table;
and obtaining the optimal capacitance value of the switch compensation capacitor when the resistance values of the mutual inductance and the system load of the magnetic coupling wireless power transmission system change according to the trained three-dimensional Q table, so that the controller adjusts the switch compensation capacitor to the optimal capacitance value.
In one embodiment, the input of the high frequency inverter module is connected with the DC power supply (V DC ) The output end of the high-frequency inversion module is connected with the primary side compensation topology and the topology input end of the transmitting coil module, and the high-frequency inversion module comprises: MOSFET switch tube (S) connected by full bridge 1 ) MOSFET switch tube (S) 2 ) MOSFET switch tube (S) 3 ) And MOSFET switch tube (S) 4 )。
In one embodiment, the transmit coil of the primary side compensation topology and transmit coil module is disposed opposite the receive coil of the receive coil and secondary side compensation topology module, the primary side compensation topology and transmit coil module including a compensation inductance (L f1 ) Switch compensation capacitor (C) f1 ) Compensating capacitor (C) 1 ) And coil (L) 1 ) The compensation inductance (L f1 ) Coil (L) 1 ) And a switch compensation capacitor (C f1 ) Is connected to the output of the high frequency inverter module as the topology input of the primary side compensation topology and the transmitter coil module, the compensation inductance (L f1 ) And the other end of the switch compensation capacitor (C f1 ) Is connected to the other end of the switch compensation capacitor (C f1 ) Is connected to one end of the switch compensation capacitor (C f1 ) Is connected to the other end of the coil (L) 1 ) Is connected to the other end of the coil (L 1 ) The topology and the transmit coils of the transmit coil module are compensated for the primary side.
In one embodiment, the output end of the receiving coil and the secondary side compensation topological module is connected with the input end of the rectifying and filtering module, and the receiving coil and the secondary side compensation topological module comprise a compensation inductance (L f2 ) Compensating capacitor (C) f2 ) Compensating capacitor (C) 2 ) And coil (L) 2 ) The coil (L) 2 ) For the receiving coil and the secondary side, the receiving coil of the topology module is compensated, the coil (L 2 ) Compensating capacitor (C) f2 ) Compensating inductance (L) f2 ) Is the output of the receiving coil and secondary compensation topology module, the coil (L 2 ) Is connected to the other end of the compensation capacitor (C 2 ) Is connected to one end of the compensation capacitor (C 2 ) Is connected to the other end of the compensation capacitor (C f2 ) Is connected with the other end of the compensation inductance (L f2 ) Is connected with the other end of the connecting rod.
In one embodiment, the rectifying and filtering module comprises a switching tube (D 1 ) Switch tube (D) 2 ) Switch tube (D) 3 ) Switch tube (D) 4 ) And filter capacitor (C) filter ) The switching tube (D 1 ) And switch tube (D) 3 ) In series, the switching tube (D 2 ) And the switching tube (D 4 ) Series-connected switching tube (D) 1 ) Sum (D) 3 ) And the switch tube (D) 2 ) Sum (D) 4 ) In parallel, a single-phase uncontrollable rectifying circuit is formed, and the single-phase uncontrollable rectifying circuit is connected with the filter capacitor (C filter ) In parallel, wherein the compensating inductance (L f2 ) Is connected to the switching tube (D) 1 ) Sum (D) 3 ) Between, the coil (L 2 ) And compensation capacitor (C) f2 ) Is connected to the switching tube (D) 2 ) Sum (D) 4 ) Between the system load and the filter capacitance (C filter ) And the rectification filter module is connected in parallel.
In one embodiment, the collecting the system power and the transmission efficiency of the magnetic coupling wireless power transmission system under the given mutual inductance variation range, the given resistance variation range of the system load and the given switch compensation capacitance variation range, to form a data set includes:
step 3.1, randomly selecting a value in a given mutual inductance variation range as a mutual inductance value of the magnetic coupling wireless power transmission system, randomly selecting a value in a given resistance variation range of a system load as a load value of the magnetic coupling wireless power transmission system, and randomly selecting a value in a given switch compensation capacitance variation range as a switch compensation capacitance value of the magnetic coupling wireless power transmission system;
step 3.2, obtaining the system power of a system load during normal operation in the current state of the magnetic coupling wireless power transmission system, obtaining the output power of a high-frequency inversion module during normal operation in the current state of the magnetic coupling wireless power transmission system, and obtaining the system efficiency according to the system power and the output power analysis;
step 3.3, recording the current mutual inductance value, the load value, the switch compensation capacitance value, the corresponding system power and system efficiency, and recording the current mutual inductance value, the load value, the switch compensation capacitance value and the corresponding system power and system efficiency as a group of data into a data set;
step 3.4, repeating the steps 3.1-3.3 to form a data set.
In one embodiment, the defining a three-dimensional Q-table of the state space, the action space, the initial state, the reward function, and the associated state space and action space of the magnetically-coupled wireless power transfer system according to the data set includes:
state space set S defining a state space a Expressed as:
S a ＝{M 1 M 2 …M i …}
wherein M is i The mutual inductance value obtained by the ith random value selection is obtained;
state space set S defining a state space a Expressed as:
S b ＝{R L1 R L2 …R Li …}
wherein R is Li The load value obtained for the ith random value selection;
the action space set a defining the action space is expressed as:
A＝{C 1 C 2 …C i …}
wherein C is i The switch compensation capacitance value obtained for the ith random value selection;
in the set of environmental states S a 、S b And on the premise of the action set A, defining a reward function as follows:
wherein R is j (M i ,R Li ,C i ) Representing that the state of any jth data set retrieval in the magnetic coupling wireless power transmission system is M i And R is Li Execute action C at time i The obtained rewards, P represents the system power output by the load side under the current circuit parameter in the magnetic coupling wireless power transmission system, P represents the expected value of the system power output by the load side, eta represents the system efficiency under the current circuit parameter in the magnetic coupling wireless power transmission system, eta represents the expected value of the system efficiency;
according to the environmental state set S a 、S b And an action set A, a three-dimensional Q table of a state space and an action space is established, wherein the three-dimensional Q table comprises three dimensions, each dimension represents one characteristic of the magnetic coupling wireless power transmission system, the first dimension represents one state in the state space, the second dimension represents the other state in the state form space, and the third dimension represents the action space.
In one embodiment, the action selection strategy of the reinforcement learning Q-learning algorithm model is an epsilon-greedy strategy, and the action selection steps of the epsilon-greedy strategy are as follows:
step 5.1: selecting an initial value of a parameter epsilon (0, 1);
step 5.2: selecting a random number rand E (0, 1);
step 5.3: if rand < ε, then randomly select an action from the set of actions in that state, otherwise, select the action with the highest Q value in the set of actions, then update the state and action to the next state and action, and update the three-dimensional Q table again.
In one embodiment, the reinforcement learning Q-learning algorithm model is expressed as:
Q k+1 (M i ,R Li ,C i )＝Q k (M i ,R Li ,C i )+α[R(M i ,R Li ,C i )+γ·maxQ k (M i+1 ,R Li+1 ,A)-Q k+1 (M i ,R Li ,C i )]wherein Q is k+1 (M i ,R Li ,C i ) Representing M in the state action value table when algorithm iterates to the (k+1) th round i Dimension and R Li Value corresponding to dimension, Q k (M i ,R Li ,C i ) Representing M in state action value table when algorithm iterates to kth round i Dimension and R Li The value corresponding to the dimension; alpha represents learning rate, and 0<α<1, a step of; gamma denotes a discount factor, considering only immediate rewards when gamma=0, and long-term rewards as immediate rewards when gamma=1; r (M) i ,R Li ,C i ) Represented in state M i R is R Li Execute action C at time i The rewards obtained; maxQ k (M i+1 ,R Li+1 A) represents the Mth in the state action value table i+1 Dimension, R Li+1 Maximum value of dimension.
According to the efficacy improving method of the double-parameter disturbance wireless power transmission system based on the Q-learning algorithm, a circuit topology structure of a magnetic coupling wireless power transmission system with a resonant network being LCC-LCC is constructed, and the magnetic coupling wireless power transmission system comprises a direct current power supply, a high-frequency inversion module, a primary side compensation topology and transmitting coil module, a receiving coil and secondary side compensation topology module, a rectification filter module and a system load which are connected in sequence; constructing a magnetic coupling wireless power transmission system according to the circuit topology structure of the magnetic coupling wireless power transmission system; acquiring a data set of the magnetic coupling wireless power transmission system under a given mutual inductance change range, a given system load resistance change range and a given switch compensation capacitance change range, defining a three-dimensional Q table of a state space, an action space, an initial state, a reward function and an associated state space and action space of the magnetic coupling wireless power transmission system according to the data set, performing iterative training on a controller of the primary side compensation topology and the switch compensation capacitance of a transmitting coil module by adopting a reinforcement learning Q-learning algorithm model until the reinforcement learning Q-learning algorithm model converges, outputting a trained three-dimensional Q table, and obtaining an optimal capacitance value of the switch compensation capacitance of the magnetic coupling wireless power transmission system when the mutual inductance and the system load resistance change according to the trained three-dimensional Q table, so that the controller adjusts the switch compensation capacitance to the optimal capacitance value. Therefore, the capacitance value of the switch compensation capacitor can be dynamically adjusted based on the Q-learning algorithm, the problem that the transmission power and efficiency are greatly reduced due to load change and mutual inductance change of the magnetic coupling resonance type wireless power transmission system is effectively solved, the output power of the magnetic coupling resonance type wireless power transmission system is effectively improved on the premise of ensuring the transmission efficiency, and the magnetic coupling resonance type wireless power transmission system has higher flexibility and precision and can adapt to complex and changeable circuit environments.
Drawings
FIG. 1 is a flow chart of a method for improving the efficiency of a dual-parameter disturbance wireless power transmission system based on a Q-learning algorithm in one embodiment;
FIG. 2 is a schematic diagram of a magnetic-coupling wireless power transfer system of an LCC-LCC in one embodiment;
FIG. 3 is a graph showing the comparison of the addition algorithm and the non-addition algorithm under the working conditions of variable mutual inductance and load of the magnetic coupling wireless power transmission system
FIG. 4 is a schematic diagram of an equivalent circuit model;
FIG. 5 is a Matlab three-dimensional simulation diagram of the magnetic coupling wireless power transmission system under the working condition that the coupling coefficient is 0.3 and the frequency is 85 kHz;
FIG. 6 is a graph showing the change of system efficiency with load resistance when the coupling coefficient is 0.3, the frequency is 85kHz, and the mutual inductance value is fixed;
FIG. 7 is a graph of system power versus load resistance for a magnetically coupled wireless power transfer system with a coupling coefficient of 0.3, a frequency of 85kHz, and a fixed mutual inductance value;
FIG. 8 is a graph showing the change of system efficiency with mutual inductance when the coupling coefficient is 0.3, the frequency is 85kHz, and the load resistance value is fixed;
FIG. 9 is a graph showing the change of system output power with mutual inductance when the coupling coefficient is 0.3, the frequency is 85kHz, and the load resistance value is fixed.
Detailed Description
The present application will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present application more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the application.
In one embodiment, as shown in fig. 1, a method for improving the efficiency of a dual-parameter disturbance wireless power transmission system based on a Q-learning algorithm is provided, which includes the following steps:
step S220, a circuit topology structure of a magnetic coupling wireless power transmission system with a resonant network being LCC-LCC is constructed, wherein the magnetic coupling wireless power transmission system comprises a direct current power supply, a high-frequency inversion module, a primary side compensation topology and transmitting coil module, a receiving coil and secondary side compensation topology module, a rectifying and filtering module and a system load which are sequentially connected.
As shown in fig. 2, in one embodiment, the input of the high frequency inverter module is connected to a dc power supply (V DC ) The output end of the high-frequency inversion module is connected with the primary side compensation topology and the topology input end of the transmitting coil module, and the high-frequency inversion module comprises: MOSFET switch S connected by full bridge 1 MOSFET switch tube S 2 MOSFET switch tube S 3 And MOSFET switch tube S 4 。
Among them, the MOSFET switching transistor refers to a Metal-Oxide-Semiconductor Field-Effect Transistor (MOSFET).
In one embodiment, a transmit coil of a primary side compensation topology and transmit coil module is disposed opposite a receive coil of a receive coil and secondary side compensation topology module, the primary side compensation topology and transmit coil module including a compensation inductance L f1 Switch compensation capacitor C f1 Compensating capacitor C 1 And coil L 1 Compensating inductance L f1 Coil L 1 And a switch compensation capacitor C f1 Is taken as the origin of one end ofThe topology input end of the side compensation topology and transmitting coil module is connected with the output end of the high-frequency inversion module, and the compensation inductance L f1 And the other end of the capacitor is connected with a switch compensation capacitor C f1 The other end of (2) is provided with a switch compensation capacitor C f1 One end of (C) is connected with the switch compensation capacitor f1 And the other end of the coil L 1 Is connected with the other end of coil L 1 The topology and the transmit coils of the transmit coil module are compensated for the primary side.
In one embodiment, the output end of the receiving coil and the secondary side compensation topological module is connected with the input end of the rectifying and filtering module, and the receiving coil and the secondary side compensation topological module comprise a compensation inductance L f2 Compensating capacitor C f2 Compensating capacitor C 2 And coil L 2 Coil L 2 Coil L for receiving coil and receiving coil of secondary compensation topology module 2 Compensating capacitor C f2 Compensating inductance L f2 One end of the coil L is the output end of the receiving coil and the secondary side compensation topology module 2 And the other end of (C) is connected with a compensation capacitor C 2 One end of the compensation capacitor C is connected with 2 And the other end of (C) is connected with a compensation capacitor C f2 Is connected with the other end of the compensation inductance L f2 Is connected with the other end of the connecting rod.
In one embodiment, the rectifying and filtering module comprises a switching tube D 1 Switch tube D 2 Switch tube D 3 Switch tube D 4 And filter capacitor C filter Switch tube D 1 And a switch tube D 3 Series connection of switch tube D 2 And a switch tube D 4 Switching tube D after series connection 1 And D 3 And the switching tube D is connected in series 2 And D 4 Connected in parallel to form a single-phase uncontrollable rectifying circuit, and a filter capacitor C filter In parallel, wherein the compensating inductance L f2 One end of (2) is connected to the switch tube D 1 And D 3 Between, coil L 2 And compensation capacitor C f2 One end of (2) is connected to the switch tube D 2 And D 4 Between the system load and the filter capacitor C filter And the parallel connection is connected with the rectifying and filtering module.
Step S240, constructing the magnetic coupling wireless power transmission system according to the circuit topology structure of the magnetic coupling wireless power transmission system.
Step S260, collecting system power and transmission efficiency correspondingly output by the magnetic coupling wireless power transmission system under the given mutual inductance change range, the given resistance change range of the system load and the given switch compensation capacitance change range to form a data set.
In one embodiment, collecting system power and transmission efficiency output by the magnetic coupling wireless power transmission system correspondingly under a given mutual inductance change range, a given resistance change range of a system load and a given switch compensation capacitance change range to form a data set, wherein the method comprises the following steps:
step 3.1, randomly selecting a value in a given mutual inductance variation range as a mutual inductance value of the magnetic coupling wireless power transmission system, randomly selecting a value in a resistance variation range of a given system load as a load value of the magnetic coupling wireless power transmission system, and randomly selecting a value in a given switch compensation capacitance variation range as a switch compensation capacitance value of the magnetic coupling wireless power transmission system;
step 3.2, obtaining the system power P of the system load during normal operation of the magnetic coupling wireless power transmission system in the current state La Obtaining output power P of high-frequency inversion module in normal operation under current state of magnetic coupling wireless power transmission system Lb Obtaining system efficiency η=p from system power and output power analysis La /P Lb ；
Step 3.3, recording the current mutual inductance value, the load value, the switch compensation capacitance value, the corresponding system power and system efficiency, and recording the current mutual inductance value, the load value, the switch compensation capacitance value and the corresponding system power and system efficiency as a group of data into a data set;
step 3.4, repeating the steps 3.1-3.3 to form a data set.
Wherein P is La System power, P, for system load Lb For output power, η is system efficiency.
It should be appreciated that in this dataset, each row represents a set of circuit parameters of the magnetically-coupled wireless power transfer system, including the current mutual inductance value, load value, and switch compensation capacitance value, as well as the corresponding system power and system efficiency. The data provides performance performances of the magnetic coupling wireless power transmission system under different mutual inductances and system loads, and data support is provided for subsequent algorithm optimization.
Step S280, defining a three-dimensional Q table of a state space, an action space, an initial state, a reward function and an associated state space and action space of the magnetic coupling wireless power transmission system according to the data set.
It should be appreciated that defining a state space and an action space of the magnetically-coupled wireless power transfer system, defining a system initial state, defining a reward function, and defining a three-dimensional Q-table models the state space and the action space of the three-dimensional Q-table. The three-dimensional Q-table correlates states with actions to store expected rewards for each load value and switch compensation capacitance value. The value of the three-dimensional Q table is updated according to the current state, the executed action, the value of the rewarding function and the expected return of the next state, and the Q-learning algorithm can predict the optimal switch compensation capacitance value under any load resistance value and mutual inductance value according to the value in the three-dimensional Q table so as to realize the maximum power transmission of the system when the parameters change.
In one embodiment, a three-dimensional Q-table defining a state space, an action space, an initial state, a reward function, and associated state and action spaces of a magnetically-coupled wireless power transfer system from a data set, comprises:
state space set S defining a state space a Expressed as:
S a ＝{M 1 M 2 …M i …}
wherein M is i The mutual inductance value obtained by the ith random value selection is obtained;
state space set S defining a state space a Expressed as:
S b ＝{R L1 R L2 …R Li …}
wherein R is Li The load value obtained for the ith random value selection;
the action space set a defining the action space is expressed as:
A＝{C 1 C 2 …C i …}
wherein C is i The switch compensation capacitance value obtained for the ith random value selection;
in the set of environmental states S a 、S b And on the premise of the action set A, defining a reward function as follows:
wherein R is j (M i ,R Li ,C i ) Representing M state of any jth data set retrieval in magnetic coupling wireless power transmission system i And R is Li Execute action C at time i The obtained rewards, P represents the system power output by the load side under the current circuit parameter in the magnetic coupling wireless power transmission system, P represents the expected value of the system power output by the load side, eta represents the system efficiency under the current circuit parameter in the magnetic coupling wireless power transmission system, and eta represents the expected value of the system efficiency;
according to the environmental state set S a 、S b And the action set A establishes a three-dimensional Q table which is related to the state space and the action space, wherein the three-dimensional Q table comprises three dimensions, each dimension represents one characteristic of the magnetic coupling wireless power transmission system, the first dimension represents one state in the state space, the second dimension represents the other state in the state form space, and the third dimension represents the action space.
It should be appreciated that any one of the action value tables represents rewards for executing a corresponding action in a corresponding state, and that by learning and iteratively updating the values of the three-dimensional Q table, the action with the highest expected return value may be selected based on the current state, thereby making decisions and controls. In summary, the three-dimensional Q-table is a three-dimensional data structure for recording states, actions and replies expected to return, and reinforcement learning is optimally performed in a multi-feature state space, thereby implementing decision and control strategies.
And step S300, based on a state space, an action space, an initial state, a reward function and a three-dimensional Q table of the magnetic coupling wireless power transmission system, performing iterative training on a primary side compensation topology and a controller of a switch compensation capacitor of a transmitting coil module by adopting a reinforcement learning Q-learning algorithm model until the reinforcement learning Q-learning algorithm model converges, and outputting a trained three-dimensional Q table.
In one embodiment, the action selection strategy of the reinforcement learning Q-learning algorithm model is an epsilon-greedy strategy, and the action selection steps of the epsilon-greedy strategy are as follows:
step 5.1: selecting an initial value of a parameter epsilon (0, 1);
step 5.2: selecting a random number rand E (0, 1);
step 5.3: if rand < ε, then randomly select an action from the set of actions in that state, otherwise, select the action with the highest Q value in the set of actions, then update the state and action to the next state and action, and update the three-dimensional Q table again.
In one embodiment, the reinforcement learning Q-learning algorithm model is expressed as:
Q k+1 (M i ,R Li ,C i )＝Q k (M i ,R Li ,C i )+α[R(M i ,R Li ,C i )+γ·maxQ k (M i+1 ,R Li+1 ,A)-Q k+1 (M i ,R Li ,C i )]wherein Q is k+1 (M i ,R Li ,C i ) Representing M in the state action value table when algorithm iterates to the (k+1) th round i Dimension and R Li Value corresponding to dimension, Q k (M i ,R Li ,C i ) Representing M in state action value table when algorithm iterates to kth round i Dimension and R Li The value corresponding to the dimension; alpha represents learning rate, and 0<α<1, a step of; gamma denotes a discount factor, considering only immediate rewards when gamma=0, and long-term rewards as immediate rewards when gamma=1; r (M) i ,R Li ,C i ) Represented in state M i R is R Li Executing actions at that timeC i The rewards obtained; maxQ k (M i+1 ,R Li+1 A) represents the Mth in the state action value table i+1 Dimension, R Li+1 Maximum value of dimension.
Initializing a state action value table, wherein the value assigned initial values in the table are all 0; the learning algorithm converges after iterative training, a trained three-dimensional Q table is output after training is carried out for set iteration times, and the controller for strengthening the learning switch compensation capacitor finds the optimal switch compensation capacitor value so that the transmission performance of the magnetic coupling wireless electric energy transmission system is improved when the mutual inductance and the load change.
Step S320, according to the trained three-dimensional Q table, the optimal capacitance value of the switch compensation capacitor of the magnetic coupling wireless power transmission system is obtained when the resistance values of the mutual inductance and the system load change, and the controller is enabled to adjust the switch compensation capacitor to the optimal capacitance value.
According to the efficacy improving method of the double-parameter disturbance wireless power transmission system based on the Q-learning algorithm, a circuit topology structure of a magnetic coupling wireless power transmission system with a resonant network being LCC-LCC is constructed, and the magnetic coupling wireless power transmission system comprises a direct current power supply, a high-frequency inversion module, a primary side compensation topology and transmitting coil module, a receiving coil and secondary side compensation topology module, a rectifying and filtering module and a system load which are connected in sequence; constructing a magnetic coupling wireless power transmission system according to a circuit topological structure of the magnetic coupling wireless power transmission system; acquiring system power and transmission efficiency which are correspondingly output by a magnetic coupling wireless power transmission system under a given mutual inductance change range, a given system load resistance change range and a given switch compensation capacitance change range, forming a data set, defining a three-dimensional Q table of a state space, an action space, an initial state, a rewarding function and an associated state space and action space of the magnetic coupling wireless power transmission system according to the data set, iteratively training a controller of a primary compensation topology and a switch compensation capacitance of a transmitting coil module by adopting a reinforcement learning Q-learning algorithm model based on the state space, the action space, the initial state, the rewarding function and the three-dimensional Q table of the magnetic coupling wireless power transmission system until the reinforcement learning Q-learning algorithm model converges, outputting a trained three-dimensional Q table, and obtaining an optimal capacitance value of the switch compensation capacitance of the magnetic coupling wireless power transmission system when the mutual inductance and the resistance of the system load change according to the trained three-dimensional Q table, so that the controller adjusts the switch compensation capacitance to an optimal capacitance value. Therefore, the capacitance value of the switch compensation capacitor can be dynamically adjusted based on the Q-learning algorithm, the problem that the transmission power and efficiency are greatly reduced due to load change and mutual inductance change of the magnetic coupling resonance type wireless power transmission system is effectively solved, the output power of the magnetic coupling resonance type wireless power transmission system is effectively improved on the premise of ensuring the transmission efficiency, and the magnetic coupling resonance type wireless power transmission system has higher flexibility and precision and can adapt to complex and changeable circuit environments.
In one example, the DC input voltage V of the system DC 400V, the driving frequency of the system is 85kHz, coil L 1 Coil L 2 Is formed by winding litz wire to reduce the resistance value of the coil, the inductance value is 217 mu H, and the capacitor C is compensated f2 70.4nF, compensation capacitor C 1 、C 2 Both were 21nF.
In one example, a set of state spaces S a Expressed as:
S a ＝{10.85,12.85,14.85,16.85,18.85,20.85,21.7,23.7,25.7,27.7,29.7,31.7,32.55,34.55,36.55,38.55,40.55,42.55,43.4,45.4,47.4,49.4,51.4,53.4,54.25,56.25,58.25,60.25,62.25,64.25,65.1,67.1,69.1,71.1,73.1,75.1,75.95}；
state space set S b Expressed as:
S b ＝{5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25}；
defining a reward function R, expressed as:
setting a learning rate alpha to be 0.1, setting a discount factor gamma to be 0.9, setting the probability epsilon of epsilon-greedy exploration to be 0.1, performing iterative training on a primary side compensation topology and a controller of a switch compensation capacitor of a transmitting coil module by adopting a reinforcement learning Q-learning algorithm model based on a state space, an action space, an initial state, a rewarding function and a three-dimensional Q table of a magnetic coupling wireless power transmission system until the reinforcement learning Q-learning algorithm model converges, and outputting a trained three-dimensional Q table. According to the trained three-dimensional Q table, obtaining the optimal capacitance value of the switch compensation capacitor of the magnetic coupling wireless power transmission system when the resistance values of the mutual inductance and the system load change, enabling the controller to adjust the switch compensation capacitor to the optimal capacitance value, and when the mutual inductance of the magnetic coupling wireless power transmission system with the resonant network being LCC-LCC is 70 mu H and the load resistance is 25Ω, the system output power is 4362W and the system transmission efficiency is 85.6%; when the system mutual inductance suddenly changes to 35 mu H and the load resistance suddenly changes to 17 omega, the system load changes and the mutual inductance is reduced to cause incomplete power transmission and reduced transmission efficiency of the system, and the system transmission efficiency is reduced to 77.85 percent and the system transmission power is reduced to 1115W; the system adjusts the switch compensation capacitance based on the Q-learning algorithm, at this time, the transmission efficiency of the system is 75.42% and the transmission power is 1775W. As shown in fig. 3, the simulation result shows that, compared with the traditional fixed capacitance method, the efficiency improvement method of the dual-parameter disturbance wireless power transmission system based on the Q-learning algorithm improves the transmission power by 600W under the condition of ensuring that the transmission efficiency of the system is basically unchanged.
The method for improving the efficiency of the dual-parameter disturbance wireless power transmission system based on the Q-learning algorithm is suitable for improving the efficiency of the dual-parameter disturbance wireless power transmission system of a wireless charging automobile, gives out the optimal design value of the switch capacitor under the current circuit parameter environment through the Q-learning algorithm in a given load resistance change range and coupling coefficient change range, and solves the problems of incomplete power transmission and unstable system caused by the fact that the equivalent resistance value of a battery in the external characteristics of the battery changes along with the battery electric quantity change and the relative position of a transmitting coil and a receiving coil deviates in the wireless charging process of the electric automobile on the premise of ensuring the transmission efficiency compared with the traditional fixed capacitance compensation mode.
Further verifying the effect of the efficiency improvement method of the double-parameter disturbance wireless power transmission system based on the Q-learning algorithm, as shown in fig. 4, respectively and equivalently converting a direct-current power supply and a high-frequency inversion module in the magnetic coupling wireless power transmission system into an alternating-current voltage source and a source resistance, and equivalently converting a rectifying and filtering module and a system load in the magnetic coupling wireless power transmission system into a single resistance load to obtain an equivalent circuit model of the magnetic coupling wireless power transmission system; according to kirchhoff voltage and current law, an equivalent circuit model is analyzed to obtain a relation of load resistance and mutual inductance of the magnetic coupling wireless power transmission system relative to system power and a relation of load resistance and mutual inductance of the magnetic coupling wireless power transmission system relative to transmission efficiency, wherein the relation is specifically as follows:
the voltage and current equation for constructing the equivalent circuit model is as follows:
the branch current expression of the equivalent circuit model is:
the relation between the load resistance and the mutual inductance of the magnetic coupling wireless power transmission system and the system power is as follows:
the relation between the load resistance and the mutual inductance of the magnetic coupling wireless power transmission system and the transmission efficiency is as follows:
wherein U is S Is an alternating voltage source, R S Is high-frequency inversionModule equivalent source resistance, I 1 Compensating inductance L for flow through primary f1 Branch current of I P Compensating capacitance C for flow through primary 1 Branch current of I S Compensating capacitance C for flow through secondary side 2 Branch current of I 0 For branch current flowing through secondary side load resistor, R L Is a resistance load, M is a mutual inductance value of the magnetic coupling wireless power transmission system, R L The resistance value of the system load is complex, and omega is the angular frequency of the magnetic coupling wireless power transmission system.
According to the equivalent circuit model, the relation between the load resistance and the mutual inductance of the magnetic coupling wireless power transmission system and the transmission efficiency, matlab three-dimensional simulation is carried out, and the simulation result is as follows:
fig. 5 is a Matlab three-dimensional simulation diagram of the system under the working condition that the coupling coefficient is 0.3 and the frequency is 85kHz, and it can be seen that the transmission power and the efficiency of the magnetic coupling wireless power transmission system with the resonant network being LCC-LCC are related to the mutual inductance and the load resistance. FIG. 6 is a graph showing the change of the system efficiency with the load resistance when the coupling coefficient is 0.3 and the frequency is 85kHz and the mutual inductance value is fixed, FIG. 7 is a graph showing the change of the system power with the load resistance when the coupling coefficient is 0.3 and the frequency is 85kHz and the mutual inductance value is fixed, FIG. 8 is a graph showing the change of the system efficiency with the mutual inductance when the coupling coefficient is 0.3 and the frequency is 85kHz and the load resistance value is fixed, and FIG. 9 is a graph showing the change of the system output power with the mutual inductance when the coupling coefficient is 0.3 and the frequency is 85kHz and the load resistance value is fixed. From this, it can be derived that: when the mutual inductance is fixed, the output power of the system is in direct proportion to the load resistance, the transmission efficiency is increased and then reduced along with the increase of the load, and the single-peak characteristic is presented; when the load resistance is fixed, the mutual inductance is positively correlated with the output power and efficiency of the system. Therefore, the application can effectively solve the problems of greatly reduced transmission power and efficiency caused by load change and mutual inductance change of the magnetic coupling resonance type wireless power transmission system by dynamically adjusting the capacitance value of the switch compensation capacitor based on the Q-learning algorithm, and effectively improve the output power of the magnetic coupling resonance type wireless power transmission system under the premise of ensuring the transmission efficiency, thereby having higher flexibility and precision.
It should be understood that, although the steps in the flowchart of fig. 1 are shown in sequence as indicated by the arrows, the steps are not necessarily performed in sequence as indicated by the arrows. The steps are not strictly limited to the order of execution unless explicitly recited herein, and the steps may be executed in other orders. Moreover, at least some of the steps in fig. 1 may include multiple sub-steps or stages that are not necessarily performed at the same time, but may be performed at different times, nor do the order in which the sub-steps or stages are performed necessarily performed in sequence, but may be performed alternately or alternately with at least a portion of other steps or sub-steps of other steps.
The technical features of the above embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.
The above examples illustrate only a few embodiments of the application, which are described in detail and are not to be construed as limiting the scope of the application. It should be noted that it will be apparent to those skilled in the art that several variations and modifications can be made without departing from the spirit of the application, which are all within the scope of the application. Accordingly, the scope of protection of the present application is to be determined by the appended claims.

Claims (9)

1. A method for improving the efficiency of a dual-parameter disturbance wireless power transmission system based on a Q-learning algorithm is characterized by comprising the following steps:
constructing a resonant network as a circuit topology structure of a magnetic coupling wireless power transmission system of LCC-LCC, wherein the magnetic coupling wireless power transmission system comprises a direct current power supply, a high-frequency inversion module, a primary side compensation topology and transmitting coil module, a receiving coil and secondary side compensation topology module, a rectifying and filtering module and a system load which are sequentially connected;
constructing a magnetic coupling wireless power transmission system according to the circuit topology structure of the magnetic coupling wireless power transmission system;
acquiring system power and transmission efficiency which are correspondingly output by the magnetic coupling wireless power transmission system under the conditions of a given mutual inductance change range, a given resistance change range of a system load and a given switch compensation capacitance change range, and forming a data set;
defining a three-dimensional Q table of a state space, an action space, an initial state, a reward function and an associated state space and action space of the magnetic coupling wireless power transmission system according to the data set;
based on a state space, an action space, an initial state, a reward function and a three-dimensional Q table of the magnetic coupling wireless power transmission system, performing iterative training on the primary side compensation topology and a controller of a switch compensation capacitor of a transmitting coil module by adopting a reinforcement learning Q-learning algorithm model until the reinforcement learning Q-learning algorithm model converges, and outputting a trained three-dimensional Q table;
and obtaining the optimal capacitance value of the switch compensation capacitor when the resistance values of the mutual inductance and the system load of the magnetic coupling wireless power transmission system change according to the trained three-dimensional Q table, so that the controller adjusts the switch compensation capacitor to the optimal capacitance value.
2. The method according to claim 1, characterized in that the input of the high-frequency inverter module is connected to the dc power source (V DC ) The output end of the high-frequency inversion module is connected with the primary side compensation topology and the topology input end of the transmitting coil module, and the high-frequency inversion module comprises: MOSFET switch tube (S) connected by full bridge 1 ) MOSFET switch tube (S) 2 ) MOSFET switch tube (S) 3 ) And MOSFET switch tube (S) 4 )。
3. The method according to claim 1, wherein the transmit coil of the primary side compensation topology and transmit coil module is disposed opposite the receive coil of the receive coil and secondary side compensation topology module, the primary side compensation topology and transmit coil module comprising a compensation inductance (L f1 ) Switch compensation capacitor (C) f1 ) Compensating capacitor (C) 1 ) And coil (L) 1 ) The compensation inductance (L f1 ) Coil (L) 1 ) And a switch compensation capacitor (C f1 ) Is connected to the output of the high frequency inverter module as the topology input of the primary side compensation topology and the transmitter coil module, the compensation inductance (L f1 ) And the other end of the switch compensation capacitor (C f1 ) Is connected to the other end of the switch compensation capacitor (C f1 ) Is connected to one end of the switch compensation capacitor (C f1 ) Is connected to the other end of the coil (L) 1 ) Is connected to the other end of the coil (L 1 ) The topology and the transmit coils of the transmit coil module are compensated for the primary side.
4. The method according to claim 1, characterized in that the output of the receiving coil and secondary compensation topology module is connected to the input of the rectifying and filtering module, the receiving coil and secondary compensation topology module comprising a compensation inductance (L f2 ) Compensating capacitor (C) f2 ) Compensating capacitor (C) 2 ) And coil (L) 2 ) The coil (L) 2 ) For the receiving coil and the secondary side, the receiving coil of the topology module is compensated, the coil (L 2 ) Compensating capacitor (C) f2 ) Compensating inductance (L) f2 ) Is the output of the receiving coil and secondary compensation topology module, the coil (L 2 ) Is connected to the other end of the compensation capacitor (C 2 ) Is connected to one end of the compensation capacitor (C 2 ) Is connected to the other end of the compensation capacitor (C f2 ) Is connected with the other end of the compensation inductance (L f2 ) Is connected with the other end of the connecting rod.
5. The method according to claim 4, characterized in thatThe rectifying and filtering module comprises a switching tube (D 1 ) Switch tube (D) 2 ) Switch tube (D) 3 ) Switch tube (D) 4 ) And filter capacitor (C) filter ) The switching tube (D 1 ) And switch tube (D) 3 ) In series, the switching tube (D 2 ) And the switching tube (D 4 ) Series-connected switching tube (D) 1 ) Sum (D) 3 ) And the switch tube (D) 2 ) Sum (D) 4 ) In parallel, a single-phase uncontrollable rectifying circuit is formed, and the single-phase uncontrollable rectifying circuit is connected with the filter capacitor (C filter ) In parallel, wherein the compensating inductance (L f2 ) Is connected to the switching tube (D) 1 ) Sum (D) 3 ) Between, the coil (L 2 ) And compensation capacitor (C) f2 ) Is connected to the switching tube (D) 2 ) Sum (D) 4 ) Between the system load and the filter capacitance (C filter ) And the rectification filter module is connected in parallel.
6. The method of claim 1, wherein the acquiring the system power and the transmission efficiency of the magnetic coupling wireless power transmission system under the given mutual inductance variation range, the given resistance variation range of the system load, and the given switch compensation capacitance variation range, and forming the data set includes:
step 3.1, randomly selecting a value in a given mutual inductance variation range as a mutual inductance value of the magnetic coupling wireless power transmission system, randomly selecting a value in a given resistance variation range of a system load as a load value of the magnetic coupling wireless power transmission system, and randomly selecting a value in a given switch compensation capacitance variation range as a switch compensation capacitance value of the magnetic coupling wireless power transmission system;
step 3.2, obtaining the system power of a system load during normal operation in the current state of the magnetic coupling wireless power transmission system, obtaining the output power of a high-frequency inversion module during normal operation in the current state of the magnetic coupling wireless power transmission system, and obtaining the system efficiency according to the system power and the output power analysis;
step 3.3, recording the current mutual inductance value, the load value, the switch compensation capacitance value, the corresponding system power and system efficiency, and recording the current mutual inductance value, the load value, the switch compensation capacitance value and the corresponding system power and system efficiency as a group of data into a data set;
step 3.4, repeating the steps 3.1-3.3 to form a data set.
7. The method of claim 1, wherein the defining a three-dimensional Q-table of the state space, the action space, the initial state, the reward function, and the associated state space and action space of the magnetically-coupled wireless power transfer system from the data set comprises:
state space set S defining a state space a Expressed as:
S a ＝{M 1 M 2 … M i …}
wherein M is i The mutual inductance value obtained by the ith random value selection is obtained;
state space set S defining a state space a Expressed as:
S b ＝{R L1 R L2 … R Li …}
wherein R is Li The load value obtained for the ith random value selection;
the action space set a defining the action space is expressed as:
A＝{C 1 C 2 … C i …}
wherein C is i The switch compensation capacitance value obtained for the ith random value selection;
in the set of environmental states S a 、S b And on the premise of the action set A, defining a reward function as follows:
wherein R is j (M i ,R Li ,C i ) Representing any jth times in the magnetic coupling wireless power transmission systemThe state of the data set is M when searching i And R is Li Execute action C at time i The obtained rewards, P represents the system power output by the load side under the current circuit parameter in the magnetic coupling wireless power transmission system, P represents the expected value of the system power output by the load side, eta represents the system efficiency under the current circuit parameter in the magnetic coupling wireless power transmission system, eta represents the expected value of the system efficiency;
according to the environmental state set S a 、S b And an action set A, a three-dimensional Q table of a state space and an action space is established, wherein the three-dimensional Q table comprises three dimensions, each dimension represents one characteristic of the magnetic coupling wireless power transmission system, the first dimension represents one state in the state space, the second dimension represents the other state in the state form space, and the third dimension represents the action space.
8. The method of claim 1, wherein the action selection strategy of the reinforcement learning Q-learning algorithm model is an epsilon-greedy strategy, and the action selection step of the epsilon-greedy strategy is as follows:
step 5.1: selecting an initial value of a parameter epsilon (0, 1);
step 5.2: selecting a random number rand E (0, 1);
step 5.3: if rand < ε, then randomly select an action from the set of actions in that state, otherwise, select the action with the highest Q value in the set of actions, then update the state and action to the next state and action, and update the three-dimensional Q table again.
9. The method of claim 1, wherein the reinforcement learning Q-learning algorithm model is expressed as:
Q k+1 (M i ,R Li ,C i )＝Q k (M i ,R Li ,C i )+α[R(M i ,R Li ,C i )+γ·maxQ k (M i+1 ,R Li +1,A)-Q k+1 (M i ,R Li ,C i )]
wherein Q is k+1 (M i ,R Li ,C i ) Representing M in the state action value table when algorithm iterates to the (k+1) th round i Dimension and R Li Value corresponding to dimension, Q k (M i ,R Li ,C i ) Representing M in state action value table when algorithm iterates to kth round i Dimension and R Li The value corresponding to the dimension; alpha represents learning rate, and 0<α<1, a step of; gamma denotes a discount factor, considering only immediate rewards when gamma=0, and long-term rewards as immediate rewards when gamma=1; r (M) i ,R Li ,C i ) Represented in state M i R is R Li Execute action C at time i The rewards obtained; max Q k (M i+1 ,R Li+1 A) represents the Mth in the state action value table i+1 Dimension, R Li+1 Maximum value of dimension.
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CN117977833A (en) * 2024-04-02 2024-05-03 中国第一汽车股份有限公司 Wireless power transmission system control method and device and computer equipment

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