Wireless charging system and method capable of reconstructing voltage

Abstract

The invention relates to the technical field of wireless charging, in particular to a wireless charging system and method capable of reconstructing voltage, and the method comprises the steps that a data collection module scans a load identification code through near field communication to obtain a battery specification parameter; the information processing module determines a target output voltage value based on a relation model of a pre-stored voltage gain, the switching frequency and the number of the parallel units; the control decision module adopts a control algorithm to dynamically solve the optimal combination of the switching frequency and the number of the parallel units, and pulse width modulation signal parameters are generated; and the output execution module drives the modularized parallel inverter circuit to work, and outputs a target voltage by adjusting the switching frequency and switching the number of parallel units. According to the invention, through combination of the modular parallel technology and the intelligent control algorithm, the problem of low charging interoperability caused by mismatching of battery parameters in a heterogeneous robot scene is solved, and self-adaptive charging of multiple types of robots by a single set of system is realized.

Description

Technical Field

[0001] This invention relates to the field of wireless charging technology, and in particular to a wireless charging system and method with reconfigurable voltage. Background Technology

[0002] Wireless charging technology is based on the principle of electromagnetic induction. In this technology, a high-frequency alternating current is passed through the transmitting coil to generate an alternating magnetic field. The receiving coil induces a current in the magnetic field due to the change in magnetic flux, and the current is rectified to charge the device. Electromagnetic induction wireless charging requires coil alignment to optimize energy transfer, while magnetic resonance technology achieves charging over longer distances by matching the resonant frequencies of the transmitting and receiving coils. This avoids physical connections and improves ease of use, making the technology widely used in mobile electronic devices and electric vehicles.

[0003] Existing wireless charging technologies suffer from the following technical challenges: In automated operation scenarios involving heterogeneous robot collaboration, existing systems employ fixed parameter designs, making it impossible to dynamically reconfigure their output voltage and frequency. Furthermore, the batteries of different robot models, such as automated guided vehicles (AGVs) and inspection drones, have inherent differences in voltage levels and charging characteristics, making it difficult for a single charging device to adapt to varying load demands and resulting in poor interoperability. For instance, wheeled handling robots and aerial monitoring drones deployed simultaneously in a smart warehouse require high-voltage constant current and low-voltage constant voltage charging modes, respectively. However, a fixed output system can only serve one type of device, forcing operators to install multiple dedicated charging facilities, which not only increases deployment costs but also limits the flexibility of operational processes. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention provides a reconfigurable voltage wireless charging system and method, solving the technical problem of low interoperability caused by mismatch between different battery models and charging device system parameters.

[0005] To solve the above-mentioned technical problems, the specific contents of the present invention are as follows: The present invention provides a wireless charging system with reconfigurable voltage, comprising a data acquisition module, an information processing module, a control decision module, and an output execution module; The data acquisition module is configured to scan the load identification code via near-field communication to obtain the battery's specifications, including the rated voltage. The information processing module is configured to receive the specification parameters and, based on a pre-stored relationship model between voltage gain, switching frequency, and the number of parallel units, determine the target output voltage value corresponding to the rated voltage in the specification parameters from the relationship model. The control decision module is configured to receive the target output voltage value determined by the information processing module, and based on the voltage gain characteristics reflected by the relationship model, use a control algorithm to dynamically solve a set of combinations of switching frequencies and the number of activated parallel units, so that the expected output voltage of the system under the combination is equal to the target output voltage value, and generate pulse width modulation signal parameters corresponding to the combination. The output execution module is configured to receive the pulse width modulation signal parameters and drive the modular parallel inverter circuit to work according to the pulse width modulation signal parameters. By adjusting the switching frequency and switching the number of parallel units, the modular parallel inverter circuit outputs the target output voltage value.

[0006] Furthermore, in the reconfigurable voltage wireless charging system of the present invention, the data acquisition module includes an integrated radio frequency reader, the integrated radio frequency reader having an operating frequency of 13.56MHz, configured to trigger a scanning action when the robot enters the charging area, and decode a passive electronic tag embedded in the battery casing through load modulation, the passive electronic tag storing battery specification data encoded in the ISO 15693 standard; The integrated RF reader transmits the decoded rated voltage and temperature threshold to the microprocessor via a serial peripheral interface. The microprocessor formats the received rated voltage and temperature threshold and outputs the specification parameters.

[0007] Furthermore, in the reconfigurable voltage wireless charging system of the present invention, the relationship model pre-stored in the information processing module is a monotonic characteristic curve of voltage gain changing with switching frequency and the number of parallel units. The information processing module receives the specification parameters output after being formatted by the microprocessor; The information processing module queries the database of optimal charging curves corresponding to the battery model in the specifications, and uses a linear interpolation algorithm to fit between discrete voltage data points in the database of optimal charging curves to generate an initial voltage setpoint. The information processing module determines whether the temperature threshold in the specification parameters exceeds the preset range. When the determination is yes, it corrects the initial voltage setpoint according to the temperature compensation logic and generates the target output voltage value. The information processing module outputs instruction parameters including the target output voltage value.

[0008] Furthermore, in the reconfigurable voltage wireless charging system of the present invention, the control decision module adopts a multi-objective optimization fuzzy PID control algorithm. The control decision module receives instruction parameters, including the target output voltage value, output by the information processing module; The multi-objective optimization fuzzy PID control algorithm takes the target output voltage value in the instruction parameters as the optimization objective, maintains the soft switching of the system as the constraint, samples the system state every 50 milliseconds, and calculates the switching frequency adjustment amount. The adjustment accuracy of the switching frequency adjustment amount is 100Hz step. The multi-objective optimization fuzzy PID control algorithm synchronously generates a parallel unit activation sequence, which follows an N+1 redundancy rule. The control decision module outputs control commands including the duty cycle and phase difference of the pulse width modulation signal.

[0009] Furthermore, in the reconfigurable voltage wireless charging system of the present invention, the output execution module includes a digital signal processor and an optocoupler-isolated drive circuit. The digital signal processor receives control commands output by the control decision module, including the duty cycle and phase difference of the pulse width modulation signal. The digital signal processor generates a synchronous pulse width modulation waveform with a corresponding duty cycle and phase difference according to the control command. The optocoupler isolation driving circuit adopts a totem pole structure, receives the synchronous pulse width modulation waveform, and converts the logic level into a driving voltage; The driving voltage is used to control the silicon carbide MOSFETs in the modular parallel inverter circuit, thereby adjusting the switching frequency and the number of parallel units.

[0010] Furthermore, in the reconfigurable voltage wireless charging system of the present invention, the modular parallel inverter circuit includes multiple parallel single-tube inverter units. Each of the single-tube inverter units integrates a current-sharing coil; The current-sharing coil suppresses circulating currents caused by differences in component parameters among the multiple parallel single-tube inverter units through magnetic integration. The leakage inductance of the current sharing coil is connected in series with the resonant inductance in the single-tube inverter unit, forming an equivalent series inductance. The equivalent series inductance participates in the resonance process of the modular parallel inverter circuit.

[0011] Furthermore, in the reconfigurable voltage wireless charging system of the present invention, the output execution module is connected to a voltage sensor and a current sensor; The voltage sensor and current sensor sample the actual output voltage and actual output current of the modular parallel inverter circuit; The output execution module converts the sampled actual output voltage and actual output current into digital feedback signals via an analog-to-digital converter and transmits them to the control decision module. The control decision module receives the digital feedback signal, compares the actual output voltage in the digital feedback signal with the target output voltage value from the information processing module, and generates an error signal. The control decision module uses the error signal to iteratively optimize the pulse width modulation signal parameters with a period of 50 milliseconds.

[0012] Furthermore, in the reconfigurable voltage wireless charging system of the present invention, the data acquisition module, information processing module, control decision module, and output execution module are connected via a controller area network bus. The controller local area network bus adopts distributed clock synchronization technology; The system is configured to switch to a safe operating mode and start a diagnostic program when a communication timeout event or parameter out-of-bounds event is detected through the controller local area network bus.

[0013] Furthermore, in the reconfigurable voltage wireless charging system of the present invention, the switching frequency adjustment range is 80kHz to 90kHz. The output voltage reconstruction range of the modular parallel inverter circuit is 200V to 340V; During the constant current charging phase, the control decision module maintains the switching frequency and the number of activated parallel units at a constant value. During the constant voltage charging phase, the control decision module switches the output voltage by adjusting the switching frequency, and the switching response time is less than 100 milliseconds. It also includes a secondary-side compensation capacitor switching circuit; When the charging mode parameter in the instruction parameters output by the information processing module indicates that constant voltage output is required, the control decision module sends a trigger signal to the secondary compensation capacitor switching circuit. The secondary-side compensation capacitor switching circuit responds to the trigger signal and connects the constant voltage compensation capacitor to the secondary-side compensation network of the wireless charging system via a relay, thereby changing the compensation network topology.

[0014] Secondly, the present invention provides a wireless charging method with reconfigurable voltage, applied to the wireless charging system with reconfigurable voltage as described above, comprising: Step 1, Scan the load identification code to obtain battery specifications: Scan the load identification code via near-field communication and decode it to obtain the battery specifications, including rated voltage and temperature threshold. Step 2, determine the target output voltage according to the specification parameters: receive the specification parameters, query the pre-stored relationship model between voltage gain, switching frequency and number of parallel units, and determine the target output voltage value corresponding to the rated voltage from the relationship model; Step 3, Generate pulse width modulation signal parameters: Based on the voltage gain characteristics reflected by the relationship model, a control algorithm is used to dynamically solve a set of combinations of switching frequency and number of activated parallel units, so that the expected output voltage of the system under the combination is equal to the target output voltage value, and pulse width modulation signal parameters corresponding to the combination are generated. Step 4, drive the power circuit to output the target voltage: drive the modular parallel inverter circuit to work according to the pulse width modulation signal parameters, and adjust the switching frequency in the range of 80kHz to 90kHz and switch the number of parallel units to make the system output a voltage that matches the target output voltage value.

[0015] Beneficial effects of this invention; This invention effectively solves the technical challenge of low interoperability of charging devices in heterogeneous robot scenarios through the synergistic innovation of modular parallel technology and intelligent control algorithms. The data acquisition module automatically identifies battery specifications using near-field communication technology; the information processing module dynamically calculates the target output voltage based on the voltage gain characteristic curve; the control decision module adjusts the switching frequency and the number of parallel units in real time through a multi-objective optimization algorithm; and the output execution module drives the modular parallel inverter circuit to achieve precise power output. This architecture allows a single charging system to adapt to robot batteries of different voltage levels, avoiding the deployment costs of multiple dedicated facilities. The magnetic integration design of the current-sharing coil and resonant inductor suppresses circulating current in the parallel units, and the closed-loop verification mechanism maintains output voltage stability through real-time feedback. The controller local area network bus ensures reliable communication between modules. The combination of the secondary-side compensation capacitor switching circuit and frequency modulation achieves seamless switching between constant current and constant voltage charging modes, retaining the simplicity of a single-tube inverter circuit while increasing power capacity through modular expansion, providing an efficient and flexible charging solution for automated operation scenarios. Attached Figure Description

[0016] To more clearly illustrate the technical solution of the present invention, the drawings used in the embodiments will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on the drawings without creative effort.

[0017] Figure 1 This is a flowchart illustrating a wireless charging method with reconfigurable voltage provided by the present invention. Detailed Implementation

[0018] To make the technical solution of the present invention clearer, the present invention will be clearly and completely described below with reference to specific embodiments and corresponding drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention. The present invention provided by various embodiments will be described in detail below with reference to the accompanying drawings. To better understand the purpose of the present invention, the present invention will be described in further detail below.

[0019] The present invention provides a wireless charging system with reconfigurable voltage, comprising a data acquisition module, an information processing module, a control decision module, and an output execution module; The data acquisition module is configured to scan the load identification code via near-field communication to obtain the battery's specifications, including the rated voltage. The information processing module is configured to receive the specification parameters and, based on a pre-stored relationship model between voltage gain, switching frequency, and the number of parallel units, determine the target output voltage value corresponding to the rated voltage in the specification parameters from the relationship model. The control decision module is configured to receive the target output voltage value determined by the information processing module, and based on the voltage gain characteristics reflected by the relationship model, use a control algorithm to dynamically solve a set of combinations of switching frequencies and the number of activated parallel units, so that the expected output voltage of the system under the combination is equal to the target output voltage value, and generate pulse width modulation signal parameters corresponding to the combination. The output execution module is configured to receive the pulse width modulation signal parameters and drive the modular parallel inverter circuit to work according to the pulse width modulation signal parameters. By adjusting the switching frequency and switching the number of parallel units, the modular parallel inverter circuit outputs the target output voltage value.

[0020] The data acquisition module scans the load identification code using near-field communication (NFC) technology to obtain the battery's specifications. Specifically, this module integrates an RFID reader operating in the 13.56MHz band. When the robot enters the charging area, it automatically triggers a scan, decoding the passive electronic tag embedded in the battery casing using load modulation. This tag stores coded data conforming to the ISO 15693 standard, including parameters such as rated voltage and temperature threshold. The decoded data is transmitted to the microprocessor via a serial peripheral interface. The microprocessor formats the received rated voltage and temperature threshold, outputting standardized specifications to provide accurate input for subsequent modules. This design allows the system to adapt to batteries from different robot models. For example, in automated warehouses, the battery voltages of automated guided vehicles (AGVs) and inspection drones differ significantly; NFC allows for rapid parameter identification, improving interoperability.

[0021] The information processing module receives the specification parameters output by the data acquisition module and determines the target output voltage value based on a pre-stored relationship model between voltage gain, switching frequency, and the number of parallel units. The relationship model is stored as a monotonic characteristic curve showing the voltage gain changing with switching frequency and the number of parallel units. The module first queries the database of optimal charging curves corresponding to the battery model and uses a linear interpolation algorithm to fit the discrete voltage data points, generating an initial voltage setpoint. Subsequently, the module determines whether the temperature threshold exceeds a preset range. If it does, it corrects the initial voltage setpoint according to temperature compensation logic, finally outputting instruction parameters including the target output voltage value. This process ensures that the output voltage setting conforms to both battery characteristics and adapts to environmental changes; for example, temperature compensation avoids overvoltage risks under high-temperature conditions, enhancing system reliability.

[0022] The control decision module employs a multi-objective optimization fuzzy PID control algorithm, using the target output voltage value output by the information processing module as the optimization objective, while maintaining the system's soft switching as a constraint. The module samples the system state every 50 milliseconds, dynamically calculates the switching frequency adjustment, and achieves adjustment accuracy in 100Hz steps. Simultaneously, it generates a parallel unit activation sequence, which follows an N+1 redundancy rule to improve fault tolerance. Based on the voltage gain characteristics reflected by the relational model, the algorithm solves for an optimal combination of switching frequency and the number of activated parallel units, ensuring the expected output voltage matches the target value, and outputs the corresponding pulse width modulation signal duty cycle and phase difference parameters. This dynamic optimization method enables the system to rapidly switch the output voltage through frequency modulation during the constant voltage charging phase, with a response time of less than 100 milliseconds, meeting the real-time requirements of robot charging.

[0023] The output execution module receives pulse width modulation (PWM) signal parameters generated by the control decision module and drives the modular parallel inverter circuit. The module includes a digital signal processor (DSP) and an optocoupler-isolated drive circuit. The DSP generates a synchronous PWM waveform with a specific duty cycle and phase difference based on control commands. The optocoupler-isolated drive circuit uses a totem-pole structure to convert logic levels into drive voltages, thereby controlling the silicon carbide MOSFETs in the modular parallel inverter circuit. By adjusting the switching frequency within the range of 80kHz to 90kHz and switching the number of parallel units, the system outputs the target output voltage value. The module also connects voltage and current sensors to sample the actual output voltage and current, converting them into digital feedback signals via an analog-to-digital converter and transmitting them to the control decision module to achieve closed-loop control. The modular parallel inverter circuit consists of multiple parallel single-tube inverter units. Each unit integrates a current-sharing coil, which suppresses circulating currents caused by differences in component parameters through magnetic integration. The leakage inductance of the current-sharing coil is connected in series with the resonant inductor to form an equivalent series inductor, participating in the circuit resonance process and improving system stability. During the constant current charging phase, the switching frequency and the number of parallel units remain constant. In the constant voltage phase, voltage reconstruction is achieved through frequency adjustment. When constant voltage output is required, the secondary-side compensation capacitor switching circuit connects the constant voltage compensation capacitor via a relay, changing the compensation network topology and further optimizing output characteristics. The system connects each module via a controller area network bus and employs distributed clock synchronization technology. Upon detecting communication timeouts or parameter out-of-bounds events, it switches to a safe mode and initiates diagnostic procedures to ensure operational safety.

[0024] The data acquisition module acquires parameters through an integrated RFID reader / writer operating in the 13.56MHz industrial, scientific, and medical frequency band. It employs load modulation technology to decode passive electronic tags conforming to the ISO 15693 standard. When the robot enters the charging area, the alternating magnetic field generated by the reader / writer antenna activates the electronic tag embedded in the battery casing. The tag chip encodes the stored battery specifications into a carrier signal via backscatter modulation. After demodulation, the reader / writer transmits the raw data, including rated voltage and temperature threshold, to the microprocessor via a serial peripheral interface. The microprocessor performs frame verification and format standardization on the data, outputting a structured set of specifications. This non-contact identification method is particularly suitable for the alternating charging needs of wheeled handling robots and inspection drones in smart warehousing scenarios, avoiding communication failures caused by physical interface wear.

[0025] The voltage gain characteristic curve built into the information processing module was obtained through experimental calibration, exhibiting a monotonic characteristic of bivariate coupling between switching frequency and the number of parallel units. After receiving the specification parameters, the module first matches the optimal charging curve database corresponding to the battery model and uses a linear interpolation algorithm to perform fitting calculations between discrete data points. When the temperature threshold exceeds the preset safety range, the temperature compensation logic dynamically corrects the initial voltage setpoint based on the material temperature coefficient, ultimately generating an instruction parameter package including the target output voltage value and the temperature compensation coefficient. This design allows the system to automatically reduce output power in high-temperature environments to prevent battery overheating damage, such as maintaining safe charging even when warehouse temperatures rise sharply in summer.

[0026] The multi-objective optimization fuzzy PID algorithm running in the control decision module uses voltage tracking accuracy and soft-switching maintenance as weighted objectives, collecting DC bus voltage and resonant current data of the inverter circuit every 50 milliseconds. The algorithm handles system state fuzziness through membership functions, calculates frequency correction values ​​with a 100Hz adjustment step accuracy, and generates parallel unit switching sequences based on N+1 redundancy rules. During the solution process, priority is given to ensuring the MOSFET zero-voltage switching condition to avoid electromagnetic interference and efficiency losses caused by hard switching. This real-time optimization mechanism enables the system to quickly respond to load changes during the constant-voltage charging phase.

[0027] The digital signal processor of the output execution module uses carrier phase-shift technology to generate synchronous pulse width modulation waveforms, and the optocoupler-isolated drive circuit provides a ±15V drive level through a totem-pole structure. When control commands are transmitted to the silicon carbide MOSFET gate, the modular parallel inverter circuit changes the power transmission characteristics by adjusting the switching frequency in the range of 80kHz to 90kHz, and simultaneously achieves power grading by switching the number of parallel units through solid-state relays. This cooperative control method can automatically select the high-power mode of three units in parallel when charging the drone battery according to its capacity characteristics, while switching to the energy-saving mode of two units when charging a small AGV.

[0028] The modular parallel inverter circuit adopts a distributed magnetic integration structure. The current-sharing coil integrated in each single-tube inverter unit achieves automatic current balancing through mutual inductance coupling. The leakage inductance of the current-sharing coil is connected in series with the resonant inductance to form an equivalent series inductance, participating in the construction of an LC series resonant network. This design ensures that each parallel unit maintains current consistency even under parameter drift, preventing individual units from being damaged by overload. Experimental data shows that under four-unit parallel operation, the current-sharing accuracy can reach within ±5%, significantly improving system reliability.

[0029] The closed-loop verification mechanism acquires output voltage and current signals through a high-precision Hall sensor, and an analog-to-digital converter converts the analog signal into a digital feedback signal at a sampling rate of 1MHz. The control decision module compares the deviation between the actual output voltage and the target value, and iteratively corrects the pulse width modulation parameters through an incremental PID algorithm. This real-time feedback mechanism enables the system to maintain a voltage regulation rate of ±1% during the constant current charging phase, effectively addressing the impact of changes in battery internal resistance.

[0030] The system communication architecture adopts the Controller Area Network (CAN) bus protocol, and the distributed clock synchronization technology uses a timestamp mechanism to ensure the timing consistency of data exchange between modules. When the bus monitor detects a communication frame loss or parameter out-of-bounds event, the system immediately switches to a safe operating mode and starts a diagnostic program. This fault protection mechanism can effectively prevent misoperation in the strong interference environment of industrial sites.

[0031] The secondary-side compensation capacitor switching circuit achieves network topology reconfiguration through a magnetically latched relay. When the charging mode parameters indicate the need for constant voltage output, the control decision module sends a trigger signal to connect the constant voltage compensation capacitor to the resonant network via the relay. This hardware-level topology switching, combined with software frequency modulation, allows the system output voltage to be continuously adjustable within the range of 200V to 340V, meeting a wide range of charging requirements from small inspection robots to large logistics AGVs. The topology switching process can be completed within 10 milliseconds without causing output current surges, ensuring a smooth transition during the charging process. Secondly, please refer to Figure 1 This invention provides a wireless charging method with reconfigurable voltage, applied to the wireless charging system with reconfigurable voltage as described above, comprising: Step 1, Scan the load identification code to obtain battery specifications: Scan the load identification code via near-field communication and decode it to obtain the battery specifications, including rated voltage and temperature threshold. Step 2, determine the target output voltage according to the specification parameters: receive the specification parameters, query the pre-stored relationship model between voltage gain, switching frequency and number of parallel units, and determine the target output voltage value corresponding to the rated voltage from the relationship model; Step 3, Generate pulse width modulation signal parameters: Based on the voltage gain characteristics reflected by the relationship model, a control algorithm is used to dynamically solve a set of combinations of switching frequency and number of activated parallel units, so that the expected output voltage of the system under the combination is equal to the target output voltage value, and pulse width modulation signal parameters corresponding to the combination are generated. Step 4, drive the power circuit to output the target voltage: drive the modular parallel inverter circuit to work according to the pulse width modulation signal parameters, and adjust the switching frequency in the range of 80kHz to 90kHz and switch the number of parallel units to make the system output a voltage that matches the target output voltage value.

[0032] This invention relates to a reconfigurable voltage wireless charging system for heterogeneous robot collaborative operation scenarios. In smart warehousing environments, automated guided vehicles (AGVs) and inspection drones are often equipped with lithium battery packs of different specifications. Existing charging devices, due to their fixed output voltage, are difficult to adapt to various types of equipment. The implementation process is described in detail below with reference to the system architecture.

[0033] The data acquisition module obtains battery parameters through an integrated RFID reader / writer operating in the 13.56MHz band. When the robot enters the charging area, it automatically activates the ISO15693 standard passive electronic tag embedded in the battery casing. The rated voltage and temperature threshold data stored within the tag are decoded by load modulation and transmitted to the microprocessor via a serial peripheral interface for data frame verification and format standardization. This non-contact identification method effectively avoids communication failures caused by physical connector wear and tear, making it particularly suitable for high-frequency industrial applications.

[0034] After receiving standardized specification parameters, the information processing module calls a pre-stored voltage gain characteristic curve to calculate the target voltage. This curve, established through experimental calibration, characterizes the coupled influence of switching frequency and the number of parallel units on voltage gain. The module first matches the optimal charging curve database corresponding to the battery model and uses a linear interpolation algorithm to fit discrete data points to generate an initial setpoint. When the temperature sensor detects that the ambient temperature exceeds a safe threshold, the temperature compensation logic dynamically corrects the output voltage value based on the battery material characteristics. This mechanism effectively prevents battery overheating damage under high-temperature conditions in summer.

[0035] The control decision module employs a multi-objective optimization fuzzy PID algorithm, with voltage tracking accuracy and soft-switching maintenance as dual optimization objectives. The module collects DC bus voltage and resonant current data every 50 milliseconds, processes the system state fuzziness through membership functions, and calculates the frequency regulation while maintaining zero-voltage switching conditions. Simultaneously, it generates a parallel unit switching sequence based on N+1 redundancy rules. This design allows the system to maintain derating operation even in the event of a single unit failure, significantly improving system reliability.

[0036] After parsing the control commands, the digital signal processor of the output execution module generates a synchronous pulse width modulation waveform using carrier phase-shifting technology. The optocoupler-isolated drive circuit provides isolated drive signals through a totem-pole structure, controlling the silicon carbide MOSFETs in the modular parallel inverter circuit. By adjusting the switching frequency within the range of 80kHz to 90kHz and combining it with the switching of the number of parallel units, the system can achieve continuous regulation of the output voltage. This cooperative control mechanism enables the system to automatically activate the multi-unit parallel mode when dealing with high-voltage AGV batteries, while switching to energy-saving operation for low-voltage AGV batteries.

[0037] The modular parallel inverter circuit adopts a distributed magnetic integration design. The current-sharing coil integrated in each single-tube inverter unit achieves automatic current balancing through mutual inductance coupling. The leakage inductance of the current-sharing coil and the resonant inductance together constitute an equivalent series inductance, participating in the construction of an LC series resonant network. This structure enables each parallel unit to maintain current sharing even when component parameters drift, effectively preventing individual units from being damaged by overload.

[0038] The system uses high-precision Hall effect sensors to collect output voltage and current in real time, and an analog-to-digital converter converts the analog signals into digital feedback signals. The control decision module compares the deviation between the actual output and the target value, and iteratively optimizes the pulse width modulation parameters using an incremental PID algorithm to form a closed-loop control circuit. This feedback mechanism enables the system to adaptively compensate for the effects of changes in battery internal resistance and maintain stable output characteristics.

[0039] The communication architecture adopts a controller area network bus protocol, and the distributed clock synchronization technology ensures the timing consistency of data exchange between modules through a timestamp mechanism. When the bus monitor detects a communication timeout or parameter out-of-bounds error, the system immediately switches to a safe operating mode and initiates a diagnostic program. This fault protection mechanism effectively improves the anti-interference capability in industrial settings.

[0040] The secondary-side compensation capacitor switching circuit achieves network topology reconfiguration through a magnetic latching relay. When the charging mode parameters indicate the need for constant voltage output, the control decision module sends a trigger signal to activate the relay. This hardware-level topology switching, combined with software frequency modulation, enables the system to smoothly transition between constant current and constant voltage charging modes, meeting the charging requirements under complex operating conditions.

[0041] The system achieves intelligent reconfiguration of the output voltage through the aforementioned modular design, and its adaptability to the charging needs of different robot models has been verified in a smart warehousing scenario. This architecture retains the structural simplicity of a single-tube inverter circuit while improving power capacity through modular parallel connection technology, providing an effective solution to the problem of interoperability in charging multiple devices.

Claims

1. A wireless charging system with reconfigurable voltage, characterized in that, It includes a data acquisition module, an information processing module, a control decision module, and an output execution module; The data acquisition module is configured to scan the load identification code via near-field communication to obtain the battery's specifications, including the rated voltage. The information processing module is configured to receive the specification parameters and, based on a pre-stored relationship model between voltage gain, switching frequency, and the number of parallel units, determine the target output voltage value corresponding to the rated voltage in the specification parameters from the relationship model. The control decision module is configured to receive the target output voltage value determined by the information processing module, and based on the voltage gain characteristics reflected by the relationship model, use a control algorithm to dynamically solve a set of combinations of switching frequencies and the number of activated parallel units, so that the expected output voltage of the system under the combination is equal to the target output voltage value, and generate pulse width modulation signal parameters corresponding to the combination. The output execution module is configured to receive the pulse width modulation signal parameters and drive the modular parallel inverter circuit to work according to the pulse width modulation signal parameters. By adjusting the switching frequency and switching the number of parallel units, the modular parallel inverter circuit outputs the target output voltage value.

2. The wireless charging system with reconfigurable voltage according to claim 1, characterized in that, The data acquisition module includes an integrated radio frequency reader / writer with an operating frequency of 13.56MHz. It is configured to trigger a scanning action when the robot enters the charging area and decode a passive electronic tag embedded in the battery casing through load modulation. The passive electronic tag stores battery specification data encoded in the ISO 15693 standard. The integrated RF reader transmits the decoded rated voltage and temperature threshold to the microprocessor via a serial peripheral interface. The microprocessor formats the received rated voltage and temperature threshold and outputs the specification parameters.

3. The wireless charging system with reconfigurable voltage according to claim 2, characterized in that, The relationship model pre-stored in the information processing module is a monotonic characteristic curve of voltage gain as a function of switching frequency and the number of parallel units. The information processing module receives the specification parameters output after being formatted by the microprocessor; The information processing module queries the database of optimal charging curves corresponding to the battery model in the specifications, and uses a linear interpolation algorithm to fit between discrete voltage data points in the database of optimal charging curves to generate an initial voltage setpoint. The information processing module determines whether the temperature threshold in the specification parameters exceeds the preset range. When the determination is yes, it corrects the initial voltage setpoint according to the temperature compensation logic and generates the target output voltage value. The information processing module outputs instruction parameters including the target output voltage value.

4. The wireless charging system with reconfigurable voltage according to claim 3, characterized in that, The control decision module employs a multi-objective optimization fuzzy PID control algorithm. The control decision module receives instruction parameters, including the target output voltage value, output by the information processing module; The multi-objective optimization fuzzy PID control algorithm takes the target output voltage value in the instruction parameters as the optimization objective, maintains the soft switching of the system as the constraint, samples the system state every 50 milliseconds, and calculates the switching frequency adjustment amount. The adjustment accuracy of the switching frequency adjustment amount is 100Hz step. The multi-objective optimization fuzzy PID control algorithm synchronously generates a parallel unit activation sequence, which follows an N+1 redundancy rule. The control decision module outputs control commands including the duty cycle and phase difference of the pulse width modulation signal.

5. The wireless charging system with reconfigurable voltage according to claim 4, characterized in that, The output execution module includes a digital signal processor and an optocoupler-isolated drive circuit; The digital signal processor receives control commands output by the control decision module, including the duty cycle and phase difference of the pulse width modulation signal. The digital signal processor generates a synchronous pulse width modulation waveform with a corresponding duty cycle and phase difference according to the control command. The optocoupler isolation driving circuit adopts a totem pole structure, receives the synchronous pulse width modulation waveform, and converts the logic level into a driving voltage; The driving voltage is used to control the silicon carbide MOSFETs in the modular parallel inverter circuit, thereby adjusting the switching frequency and the number of parallel units.

6. The wireless charging system with reconfigurable voltage according to claim 5, characterized in that, The modular parallel inverter circuit includes multiple parallel single-tube inverter units; Each of the single-tube inverter units integrates a current-sharing coil; The current-sharing coil suppresses circulating currents caused by differences in component parameters among the multiple parallel single-tube inverter units through magnetic integration. The leakage inductance of the current sharing coil is connected in series with the resonant inductance in the single-tube inverter unit, forming an equivalent series inductance. The equivalent series inductance participates in the resonance process of the modular parallel inverter circuit.

7. The wireless charging system with reconfigurable voltage according to any one of claims 1 to 6, characterized in that, The output execution module is connected to a voltage sensor and a current sensor; The voltage sensor and current sensor sample the actual output voltage and actual output current of the modular parallel inverter circuit; The output execution module converts the sampled actual output voltage and actual output current into digital feedback signals via an analog-to-digital converter and transmits them to the control decision module. The control decision module receives the digital feedback signal, compares the actual output voltage in the digital feedback signal with the target output voltage value from the information processing module, and generates an error signal. The control decision module uses the error signal to iteratively optimize the pulse width modulation signal parameters with a period of 50 milliseconds.

8. The wireless charging system with reconfigurable voltage according to claim 7, characterized in that, The data acquisition module, information processing module, control decision module, and output execution module are connected via a controller local area network bus. The controller local area network bus adopts distributed clock synchronization technology; The system is configured to switch to a safe operating mode and start a diagnostic program when a communication timeout event or parameter out-of-bounds event is detected through the controller local area network bus.

9. The wireless charging system with reconfigurable voltage according to claim 8, characterized in that, The switching frequency can be adjusted from 80kHz to 90kHz. The output voltage reconstruction range of the modular parallel inverter circuit is 200V to 340V; During the constant current charging phase, the control decision module maintains the switching frequency and the number of activated parallel units at a constant value. During the constant voltage charging phase, the control decision module switches the output voltage by adjusting the switching frequency, and the switching response time is less than 100 milliseconds. It also includes a secondary-side compensation capacitor switching circuit; When the charging mode parameter in the instruction parameters output by the information processing module indicates that constant voltage output is required, the control decision module sends a trigger signal to the secondary compensation capacitor switching circuit. The secondary-side compensation capacitor switching circuit responds to the trigger signal and connects the constant voltage compensation capacitor to the secondary-side compensation network of the wireless charging system via a relay, thereby changing the compensation network topology.

10. A wireless charging method with reconfigurable voltage, applied to a wireless charging system with reconfigurable voltage as described in any one of claims 1 to 9, characterized in that, include: Step 1, Scan the load identification code to obtain battery specifications: Scan the load identification code via near-field communication and decode it to obtain the battery specifications, including rated voltage and temperature threshold. Step 2, determine the target output voltage according to the specification parameters: receive the specification parameters, query the pre-stored relationship model between voltage gain, switching frequency and number of parallel units, and determine the target output voltage value corresponding to the rated voltage from the relationship model; Step 3, Generate pulse width modulation signal parameters: Based on the voltage gain characteristics reflected by the relationship model, a control algorithm is used to dynamically solve a set of combinations of switching frequency and number of activated parallel units, so that the expected output voltage of the system under the combination is equal to the target output voltage value, and pulse width modulation signal parameters corresponding to the combination are generated. Step 4, drive the power circuit to output the target voltage: drive the modular parallel inverter circuit to work according to the pulse width modulation signal parameters, and adjust the switching frequency in the range of 80kHz to 90kHz and switch the number of parallel units to make the system output a voltage that matches the target output voltage value.

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