Derivative works

Defensive Disclosure: Derivative Works of US Patent 8013568

This document details derivative works and technical disclosures based on US Patent 8013568, titled "Contact-less chargeable battery and charging device, battery charging set, and charging control method thereof." The intent is to establish prior art for various extensions, integrations, and modifications of the core inventive concepts, rendering future incremental improvements by competitors obvious or non-novel.

Derivatives of Claims 1 and 7: Contact-less Chargeable Battery / Charging Circuit Module

The core of Claims 1 and 7 describes a contact-less chargeable battery (or its charging circuit module) featuring a high frequency AC current inducing unit, a rectifier, a constant voltage/constant current (CV/CC) supplier, and an overvoltage monitoring unit that wirelessly transmits monitoring results to the charging device to induce a change in magnetic field intensity.

1. Material & Component Substitution

Enabling Description:
Instead of traditional copper wire coils, the high-frequency AC current inducing unit (secondary coil) utilizes carbon nanotube (CNT) film windings, laminated with a flexible polymer substrate, enabling enhanced flexibility and reduced weight. The rectifier integrates gallium nitride (GaN) high-electron-mobility transistors (HEMTs) configured as active rectifiers for improved efficiency at very high switching frequencies and reduced reverse recovery losses. The constant voltage/constant current supplier incorporates solid-state polymer capacitors for high volumetric efficiency and improved ripple current handling. For the overvoltage monitoring unit, the first and second voltage detectors employ thin-film thermistor arrays directly coupled to voltage regulation points, leveraging temperature coefficients for indirect voltage anomaly detection, and the wireless transmitting unit is realized using a flexible patch antenna printed with silver nanoparticle ink on a polyimide substrate, operating at 13.56 MHz.

classDiagram
    class HighFrequencyACInducingUnit {
        +CarbonNanotubeFilmCoil
        +FlexiblePolymerSubstrate
    }
    class Rectifier {
        +GaN_HEMT_ActiveRectifiers
    }
    class ConstantVoltageCurrentSupplier {
        +SolidStatePolymerCapacitors
    }
    class OvervoltageMonitoringUnit {
        +ThinFilmThermistorDetectors
        +FlexiblePatchAntenna
        +SilverNanoparticleInk
    }
    HighFrequencyACInducingUnit --> Rectifier
    Rectifier --> ConstantVoltageCurrentSupplier
    ConstantVoltageCurrentSupplier --> OvervoltageMonitoringUnit
    OvervoltageMonitoringUnit --> HighFrequencyACInducingUnit : Wireless_Feedback

2. Operational Parameter Expansion

Enabling Description:

• Nanoscale/Microscale Integration: The charging circuit module is implemented as a System-on-Chip (SoC) for powering micro-electromechanical systems (MEMS) or implantable biosensors. The secondary coil is a micro-fabricated spiral inductor with 50 µm trace widths on a silicon substrate, optimized for inductive coupling at 200 MHz. The rectifier, CV/CC supplier, and overvoltage monitoring unit are integrated on-chip using 65nm CMOS technology, capable of processing microwatt-level power. The overvoltage detection threshold is set to 10 mV.
• Industrial Scale Application: For charging large battery banks in grid-scale energy storage systems, the secondary coil is a multi-turn, air-core Litz wire coil with a 2-meter diameter, designed for 20 kW power transfer at 50 kHz. The rectifier uses SCR-based phase-controlled rectification for robustness. The CV/CC supplier handles 100 V / 200 A. The overvoltage monitoring unit employs isolated, high-precision Hall-effect current sensors and voltage transducers, communicating results over a secure industrial Wi-Fi (IEEE 802.11ah, HaLow) link during 5-second power pauses every minute.
• Extreme Temperature Operation: A battery charging circuit for high-temperature geothermal sensors (up to 250°C). The secondary coil utilizes high-temperature magnet wire with polyimide insulation and a ferrite core stable at 300°C. SiC-based Schottky diodes form the rectifier. The CV/CC supplier incorporates high-temperature ceramic capacitors and SiC power FETs. The overvoltage monitoring unit uses high-temperature operational amplifiers and specialized data communication links (e.g., acoustic or high-frequency infrared through sapphire windows) to transmit data to the external charging device.

flowchart TD
    A[Start Charging] --> B{Scale?};
    B -- Nanoscale --> B1[Micro-fabricated Coils, 200MHz, µW];
    B1 --> B2[CMOS Integrated Circuit, 10mV Overvoltage Threshold];
    B -- Industrial Scale --> C1[2m Litz Wire Coil, 50kHz, 20kW];
    C1 --> C2[SCR Rectifier, 100V/200A CV/CC];
    C2 --> C3[Industrial Wi-Fi Comm during 5s Pause];
    B -- Extreme Temp --> D1[High-Temp Magnet Wire Coil, Ferrite Core @300°C];
    D1 --> D2[SiC Diodes & FETs, Ceramic Capacitors];
    D2 --> D3[Acoustic/IR Comm, High-Temp OpAmps];

3. Cross-Domain Application

Enabling Description:

• Medical Implants: For wirelessly charging implantable glucose sensors, the circuit module (implant side) features a hermetically sealed, titanium-encased micro-coil for power reception, operating at 6.78 MHz. The overvoltage monitoring unit, crucial for patient safety, detects voltage excursions above 50 mV and transmits coded signals via the MICS (Medical Implant Communication Service) band (402-405 MHz) during intermittent pauses of inductive power, ensuring minimal tissue heating and precise power delivery.
• Underwater Robotics: Integrated into autonomous underwater vehicle (AUV) docking stations for charging. The secondary coil is encapsulated in a high-pressure, corrosion-resistant ceramic-polymer composite. The inductive frequency is lowered to 50 kHz for better propagation through water. The overvoltage monitoring unit converts detected overvoltage signals into acoustic data packets, transmitted via an ultrasonic transducer (e.g., at 100 kHz) during power pauses, to a corresponding acoustic receiver on the charging station.
• Agricultural Sensors: For field-deployed soil moisture and nutrient sensors. The charging circuit module is ruggedized against environmental ingress (IP68 rating). The secondary coil is molded into the sensor casing. Overvoltage detection results are transmitted via a LoRaWAN module (e.g., at 915 MHz in North America) during periodic sleep cycles (acting as power pauses) to a central gateway, allowing efficient monitoring of distributed sensor battery health across large farming areas.

sequenceDiagram
    ChargerDevice->>+BatteryCircuit: Inductive_Power (Intermittent)
    BatteryCircuit->>BatteryCell: Charge_Cell (CV/CC)
    alt Overvoltage Detected
        BatteryCircuit->>BatteryCircuit: Monitor_Overvoltage
        BatteryCircuit-->>-ChargerDevice: Wireless_Feedback (During Pause)
        ChargerDevice->>ChargerDevice: Adjust_Power
    else Normal Operation
        BatteryCircuit->>BatteryCircuit: Continue_Monitoring
    end
    Note right of ChargerDevice: Medical Implant (MICS)
    Note right of ChargerDevice: Underwater Robotics (Acoustic)
    Note right of ChargerDevice: AgTech Sensors (LoRaWAN)

4. Integration with Emerging Tech

Enabling Description:

• AI-driven Optimization: An on-board AI module, implemented as a tinyML model on the battery's microprocessor, continuously analyzes real-time voltage and current profiles at the CV/CC supplier, alongside historical charging data. It predicts impending overvoltage conditions based on learned patterns and proactively generates a "predictive adjustment request" signal, including recommended power reduction parameters, transmitted wirelessly to the charging device during the intermittent power pause, anticipating and mitigating overvoltage events before they become critical.
• IoT Sensors for Real-time Monitoring: The overvoltage monitoring unit is augmented with additional integrated IoT sensors: a solid-state temperature sensor within the battery cell, a MEMS accelerometer for detecting physical impacts, and a humidity sensor. The combined monitoring result, a JSON payload including voltage status, temperature, and acceleration data, is transmitted wirelessly (e.g., via Wi-Fi Direct at 2.4 GHz) during charging pauses to the charging device, which then relays this comprehensive battery health report to a cloud-based IoT platform for fleet management and predictive maintenance.
• Blockchain for Supply Chain Verification: Each charging cycle, initiated by the battery's detection and confirmation, results in a cryptographically signed "charging event" transaction by the battery's secure element. This transaction includes the initial power request, any subsequent overvoltage monitoring results, and the charger's response. This event is wirelessly communicated to the charging device during a pause, which then writes the validated transaction to a permissioned blockchain, creating an immutable ledger of battery health and usage for warranty claims and supply chain traceability.

graph TD
    A[Battery Charging Circuit] --> B{AI Module};
    B -- Predicted Overvoltage --> C[Wireless Transmitting Unit];
    A --> D{IoT Sensors};
    D -- Comprehensive Data --> C;
    A --> E{Blockchain Secure Element};
    E -- Signed Transaction --> C;
    C -- Wireless Comm (Pause) --> F[External Charging Device];
    F --> G[Cloud IoT Platform];
    F --> H[Blockchain Network];
    H --> I[Supply Chain / Warranty Mgmt];

5. The "Inverse" or Failure Mode

Enabling Description:

• Safe-Fail Isolation Mode: Upon detection of a severe, persistent overvoltage condition at the CV/CC supplier (exceeding a critical threshold for more than 100ms), or an internal circuit fault (e.g., short circuit in the rectifier), the battery's microprocessor immediately triggers a normally-open solid-state relay (SSR) to physically disconnect the battery cell from the entire charging circuit. Concurrently, it wirelessly transmits a "critical fault: safe isolation activated" emergency beacon with a unique device ID and fault code via its wireless transmitting unit during the next available communication window.
• Low-Power Trickle Charge Mode: If an overvoltage condition is detected but is moderate and transient, or if the magnetic coupling quality falls below a defined threshold, the battery's overvoltage monitoring unit transmits a "low-power mode requested" signal. The CV/CC supplier then automatically limits its current output to a safe, minimal trickle charge rate (e.g., C/100), sufficient to maintain charge but prevent further stress. The wireless transmitting unit continuously attempts to re-establish full feedback communication while remaining in this safe mode.
• Limited-Functionality Degradation Mode: The CV/CC supplier is designed with redundant parallel regulation stages. If the overvoltage monitoring unit detects degradation or an internal fault in one of these stages (e.g., current drift), the microprocessor dynamically reconfigures the CV/CC supplier to bypass the faulty stage. The battery then operates in a "limited-functionality" charging mode at reduced maximum current (e.g., 70% of nominal) and transmits a "degraded performance alert" to the charging device during communication pauses, allowing for continued, albeit slower, charging.

stateDiagram-v2
    [*] --> Idle
    Idle --> Charging: Start_Inductive_Power
    Charging --> Monitoring: Power_On_Delay
    Monitoring --> OvervoltageDetected: Voltage_Exceeds_Threshold
    OvervoltageDetected --> SafeFailIsolation: Critical_Overvoltage_Persistent
    SafeFailIsolation --> [*]: Disconnect_Battery_Cell
    OvervoltageDetected --> TrickleChargeMode: Moderate_Overvoltage_Transient
    TrickleChargeMode --> Charging: Communication_Re-established
    OvervoltageDetected --> LimitedFunctionality: Component_Degradation
    LimitedFunctionality --> Charging: Continue_Reduced_Charging
    Monitoring --> Charging: No_Overvoltage
    Monitoring --> Idle: Charging_Complete_or_Stopped

Derivatives of Claim 13: Contact-less Charging Device

Claim 13 describes a contact-less charging device comprising a magnetic field generating unit, a high frequency power driving unit, and a charging power adjusting unit that receives monitoring results from the battery and controls the high frequency power driving unit.

1. Material & Component Substitution

Enabling Description:
The magnetic field generating unit (primary coil) utilizes amorphous metal ribbon windings, encapsulated in a high-thermal-conductivity ceramic matrix for improved magnetic coupling efficiency and reduced eddy current losses. The high-frequency power driving unit employs a multi-level inverter topology with silicon carbide (SiC) MOSFETs, enabling switching frequencies up to 1 MHz and highly granular control over the output waveform. The charging power adjusting unit integrates a software-defined radio (SDR) platform (e.g., using a Zynq SoC) for the wireless receiving unit, allowing dynamic reconfiguration of modulation schemes (e.g., FSK, PSK) and adaptive frequency hopping (e.g., 902-928 MHz ISM band) based on detected interference, ensuring robust communication. The power supply's overvoltage filter incorporates active rectification and power factor correction (PFC) using advanced resonant converters.

classDiagram
    class MagneticFieldGeneratingUnit {
        +AmorphousMetalRibbonCoil
        +CeramicMatrixEncapsulation
    }
    class HighFrequencyPowerDrivingUnit {
        +SiC_MOSFET_MultiLevelInverter
        +1MHz_Switching
    }
    class ChargingPowerAdjustingUnit {
        +SDR_WirelessReceivingUnit
        +DynamicModulation
        +AdaptiveFrequencyHopping
    }
    class PowerSupply {
        +ActivePFC_ResonantConverter
    }
    PowerSupply --> HighFrequencyPowerDrivingUnit
    HighFrequencyPowerDrivingUnit --> MagneticFieldGeneratingUnit
    ChargingPowerAdjustingUnit ..> HighFrequencyPowerDrivingUnit : Controls
    ChargingPowerAdjustingUnit <.. MagneticFieldGeneratingUnit : Feedback(Wireless)

2. Operational Parameter Expansion

Enabling Description:

• High-Power Industrial Charging: A charging device designed for high-power electric vehicle (EV) charging. The primary coil is a large, liquid-cooled, flat-plate inductor embedded in the pavement, capable of 50 kW power transfer at 85 kHz. The high-frequency power driving unit consists of modular, paralleled IGBT-based inverters with redundant power paths for reliability. The charging power adjusting unit is a real-time Linux-based industrial controller, receiving overvoltage feedback from the EV's battery management system via a secure Wi-Fi 6 (IEEE 802.11ax) link, coordinating power adjustments with grid load management systems.
• Miniaturized/Wearable Charging: A charging device for smart rings or medical patches. The magnetic field generating unit is a micro-coil (e.g., 10mm diameter) manufactured via laser micromachining on a flexible substrate. The high-frequency power driving unit is a compact Class-E amplifier integrated onto a single PMIC (Power Management IC), operating at 13.56 MHz for milliwatt-level charging. The charging power adjusting unit is a tiny microcontroller (MCU) that uses Bluetooth Low Energy (BLE) for receiving feedback and making fine-grained pulse-width modulation adjustments.
• High-Frequency Multi-Resonant Charging: A charging device utilizing multiple resonant primary coils (e.g., three coils arranged in a triangular pattern) to create a larger, more flexible charging zone. The system operates at 10 MHz, using highly efficient Class-D amplifiers in the high-frequency power driving unit. The charging power adjusting unit dynamically tunes the impedance matching networks for each primary coil and adjusts their relative phases based on overvoltage feedback and spatial positioning data from the battery, optimizing power delivery and magnetic field homogeneity across the charging surface.

flowchart TD
    A[Start Charging Device] --> B{Application Scale?};
    B -- High-Power EV --> B1[Liquid-Cooled Primary Coil, 50kW @ 85kHz];
    B1 --> B2[Modular IGBT Inverters, Real-time Linux Controller];
    B2 --> B3[Wi-Fi 6 Feedback to Grid Management];
    B -- Miniaturized Wearable --> C1[Micro-Coil, Laser Micromachined, 10mm];
    C1 --> C2[Class-E PMIC @ 13.56MHz, mW Power];
    C2 --> C3[MCU with BLE Feedback, PWM Adjustment];
    B -- Multi-Resonant --> D1[Multiple Resonant Primary Coils @ 10MHz];
    D1 --> D2[Class-D Amplifiers, Dynamic Impedance Matching];
    D2 --> D3[Adjust Phase/Power based on Feedback/Position];

3. Cross-Domain Application

Enabling Description:

• Autonomous Vehicle Infrastructure: Charging infrastructure embedded in smart roads. The magnetic field generating unit consists of modular primary coils integrated within road segments, activated as an autonomous vehicle approaches. The high-frequency power driving unit (e.g., 20 kW per segment) is ruggedized for outdoor conditions. The charging power adjusting unit communicates with the vehicle's onboard systems via DSRC (Dedicated Short Range Communications, IEEE 802.11p) or 5G V2X, receiving battery state and overvoltage alerts in real-time, enabling dynamic power adjustments for vehicles in motion, ensuring continuous, safe energy transfer.
• Smart Furniture/Retail Displays: Wireless charging elements integrated into coffee tables, desks, or retail product display stands. The primary coil is an aesthetically hidden, flat-panel coil underneath the surface. The high-frequency power driving unit is a low-profile, energy-efficient converter. The charging power adjusting unit uses a multi-protocol wireless module (e.g., supporting Qi, BLE, and Zigbee) to detect and communicate with various devices (smartphones, tablets, smart home gadgets), receiving overvoltage feedback and adjusting charging power to prevent damage to diverse client devices, while also supporting user presence detection to save energy.
• Aerospace Maintenance Docks: A charging device for autonomous inspection drones or internal sensors within aircraft during hangar maintenance. The magnetic field generating unit is a robotic arm-mounted primary coil that can precisely position itself. The high-frequency power driving unit is hardened against electromagnetic interference (EMI) and operates with redundant power supplies. The charging power adjusting unit communicates with the drone's flight controller and battery management system via a secure, high-bandwidth Wi-Fi 6E link, receiving overvoltage alerts and diagnostic data, enabling precise and fault-tolerant power delivery for critical avionic applications.

sequenceDiagram
    ChargerDevice->>+ClientDevice: Inductive_Power (Intermittent)
    ClientDevice->>ClientDevice: Battery_Charging
    alt Overvoltage Detected
        ClientDevice->>ClientDevice: Monitor_Overvoltage
        ClientDevice-->>-ChargerDevice: Wireless_Feedback (During Pause)
        ChargerDevice->>ChargerDevice: Adjust_Power
    else Normal Operation
        ClientDevice->>ClientDevice: Continue_Monitoring
    end
    Note right of ChargerDevice: AV Road (DSRC/5G V2X)
    Note right of ChargerDevice: Smart Furniture (Qi/BLE/Zigbee)
    Note right of ChargerDevice: Aerospace Dock (Wi-Fi 6E)

4. Integration with Emerging Tech

Enabling Description:

• AI-driven Predictive Charging: The charging power adjusting unit integrates a deep learning inference engine. This AI analyzes historical charging data, real-time battery monitoring results (including temperature, charge rate, and overvoltage events), and ambient environmental conditions. It uses a predictive model to adjust the high-frequency AC current's pulse width, frequency, and amplitude before explicit overvoltage alerts are received, aiming to optimize battery health and charging speed while proactively preventing stress.
• IoT Sensors for Environmental Adaptation: The charging device incorporates a suite of IoT sensors: an ultrasonic proximity sensor to detect foreign objects on the charging surface, an ambient temperature/humidity sensor, and an electromagnetic field (EMF) leakage detector. This environmental data is fed into the charging power adjusting unit, allowing it to adapt charging parameters (e.g., reducing power if a metallic object is detected, or adjusting frequency to minimize EMF leakage) for enhanced safety, efficiency, and environmental compliance.
• Blockchain for Energy Transaction Auditing: The charging device operates as a verifiable node in a decentralized energy network. Each charging session, including the initial power handshake, subsequent power adjustments based on battery feedback, and final charge completion, is recorded as a cryptographically signed transaction by the charging power adjusting unit. These transactions are logged onto a public or consortium blockchain, providing an immutable audit trail for energy consumption, facilitating micro-billing, and enabling transparent regulatory oversight.

graph TD
    A[Battery Monitoring Result] --> B{Charging Power Adjusting Unit};
    C[Environmental IoT Sensors] --> B;
    B -- AI Analysis --> D[High Frequency Power Driving Unit Control];
    B -- Blockchain Tx --> E[Blockchain Network];
    D -- Adjust Power --> F[Magnetic Field Generating Unit];
    E --> G[Auditing / Billing / Compliance];

5. The "Inverse" or Failure Mode

Enabling Description:

• Emergency Power-Down with Redundancy: Upon receiving a critical overvoltage or thermal runaway alert from a battery, or detecting an internal fault (e.g., primary coil short, inverter failure), the charging power adjusting unit immediately commands the high-frequency power driving unit to cease all AC output. Additionally, it triggers a physical disconnect (e.g., a fast-acting circuit breaker or contactor) on the main power line to the entire charging system, ensuring absolute power cessation. A backup battery-powered communication module then broadcasts a "system fault: emergency shutdown" message via an auxiliary radio frequency.
• Low-Power Polling/Discovery Mode: When no battery is actively charging or detected, the charging device enters an ultra-low-power polling mode. The high-frequency power driving unit applies minimal, very short (e.g., 10 µs) AC pulses to the primary coil every 5 seconds. This reduced power mode is sufficient to detect the presence of a secondary coil and receive initial connection requests without significant energy consumption or electromagnetic emissions. If no response, it remains in this deep-sleep, intermittent polling state.
• Limited Current Diagnostic Mode: If the charging power adjusting unit receives inconsistent, ambiguous, or garbled monitoring results from a battery (indicating a potential communication or battery fault), it defaults to a very low, constant current diagnostic charging mode (e.g., 5W maximum output). This allows for a minimal, safe power transfer while the charging device attempts to re-establish stable communication or perform diagnostic checks on the receiving battery, preventing further damage while awaiting clear feedback.

stateDiagram-v2
    [*] --> Idle
    Idle --> Polling: No_Battery_Detected
    Polling --> Charging: Battery_Detected
    Charging --> Monitoring: Power_Transfer
    Monitoring --> FaultDetected: Critical_Overvoltage_or_Internal_Fault
    FaultDetected --> EmergencyPowerDown: Immediate_Shutdown
    EmergencyPowerDown --> [*]: Physical_Disconnect
    Monitoring --> DiagnosticMode: Ambiguous_Feedback_or_Comm_Loss
    DiagnosticMode --> Charging: Clear_Feedback_Re-established
    DiagnosticMode --> FaultDetected: Diagnostic_Fails
    Monitoring --> Idle: Charging_Complete_or_Removed

Derivatives of Claim 21: Battery Charging Set

Claim 21 outlines a battery charging set comprising both the battery and the charging device, emphasizing intermittent operation and synchronized wireless communication for overvoltage monitoring.

1. Material & Component Substitution

Enabling Description:
The primary and secondary coils of the charging set employ flexible, multi-layer printed circuit board (FPCB) inductors with integrated thin-film magnetic shielding using amorphous metal foils, allowing for highly conformal designs and reduced leakage flux. The high-frequency power driving unit in the charger and the rectifier/CV/CC supplier in the battery utilize System-in-Package (SiP) modules comprising integrated GaN power components for both power conversion and rectification, optimizing space and efficiency. The wireless communication antennae on both sides are implemented as co-planar waveguide (CPW) structures etched directly onto the FPCB, enabling simultaneous inductive power transfer and low-power data communication on distinct frequency bands during precisely synchronized intermittency windows.

classDiagram
    class Battery {
        +FPCB_SecondaryCoil
        +SiP_GaN_Rectifier_CV_CC
        +CPW_Antenna
        +OvervoltageMonitoringUnit
    }
    class ChargingDevice {
        +FPCB_PrimaryCoil
        +SiP_GaN_PowerDriver
        +CPW_Antenna
        +ChargingPowerAdjustingUnit
    }
    Battery -- ChargingDevice : Inductive_Power_Transfer
    Battery <--> ChargingDevice : Wireless_Comm_Feedback

2. Operational Parameter Expansion

Enabling Description:

• Dynamic Intermittency Profile: The charging set dynamically adjusts the duration of charging (Δt A) and pause (Δt B) regions based on real-time factors. For example, Δt B is extended to 200 ms for comprehensive diagnostic data transmission when battery state-of-health (SOH) is below 50%, while it shrinks to 10 ms for rapid power adjustments when approaching full charge, all orchestrated by a fuzzy logic controller in the charging power adjusting unit based on incoming battery data.
• Multi-Frequency Inductive Coupling: The charging set utilizes a multi-frequency inductive power transfer system. The primary coil applies high-frequency AC current at two distinct frequencies simultaneously (e.g., 80 kHz for bulk power and 200 kHz for fine-tuned power delivery). The battery's secondary coil is designed with two resonant circuits to receive power from both frequencies. The overvoltage monitoring unit wirelessly feeds back data, allowing the charging power adjusting unit to independently modulate power on each frequency during synchronized multi-band communication pauses, optimizing efficiency and power distribution.
• Extreme Environmental Endurance: The charging set is designed for operation in harsh environments, e.g., polar research stations at -60°C. All components are selected for cryogenic operation. The inductive coils are encased in a frost-resistant polymer. The wireless communication for feedback uses frequency-hopping spread spectrum (FHSS) on the 2.4 GHz band, with redundant transmitters/receivers on both sides, to maintain robust data links despite extreme cold affecting RF propagation and component stability.

flowchart TD
    A[Start Charging Set] --> B{Operation Mode?};
    B -- Dynamic Intermittency --> B1[Fuzzy Logic Adjusts ΔtA/ΔtB];
    B1 --> B2[Longer Pause for Diagnostics (Low SOH)];
    B1 --> B3[Shorter Pause for Rapid Adjustment (High SOH)];
    B -- Multi-Frequency --> C1[Charger Emits @ F1 & F2];
    C1 --> C2[Battery Receives @ F1 & F2];
    C2 --> C3[Feedback Adjusts Power per Frequency (F1, F2)];
    B -- Extreme Environment --> D1[Cryogenic Components, Frost-Resistant Coils];
    D1 --> D2[FHSS 2.4GHz with Redundancy];

3. Cross-Domain Application

Enabling Description:

• Smart City Public Charging: Public furniture (benches, lampposts) equipped with the charging set for personal devices. The charging device coordinates with a city-wide smart grid management system. The battery in a user's device monitors overvoltage and transmits feedback during intermittent charging pauses. The charging device, in response, adjusts power but also receives signals from the grid to reduce output during peak energy demand, balancing user convenience with municipal energy conservation.
• Space Exploration Robotics: A charging set deployed on a lunar rover to charge its internal batteries. Both the charging device (docking station) and the battery (rover) are radiation-hardened and vacuum-sealed. Intermittent charging cycles are synchronized with solar panel availability. The overvoltage monitoring unit transmits data via a secure, laser-based free-space optical communication link during charging pauses, crucial for fault detection in the extreme space environment, enabling precise power adjustment from the docking station.
• Hospital Medical Equipment: Charging sets for portable medical diagnostic tools (e.g., ultrasound probes, mobile vital sign monitors) within a hospital environment. The inductive charging and feedback communication are designed to meet stringent electromagnetic compatibility (EMC) standards to prevent interference with other medical devices. The overvoltage monitoring unit in the medical device's battery ensures safe charging, with communication during pauses utilizing secure Ultra-Wideband (UWB) to transmit battery status and overvoltage alerts to the charging device, integrating with the hospital's asset tracking system.

sequenceDiagram
    ChargerDevice->>+BatteryDevice: Inductive_Power (Intermittent)
    BatteryDevice->>BatteryDevice: Monitor_Overvoltage
    BatteryDevice-->>-ChargerDevice: Wireless_Feedback (During Pause)
    ChargerDevice->>ChargerDevice: Adjust_Power
    ChargerDevice->>GridManagement: Report_Status / Receive_Demand
    Note right of ChargerDevice: Smart City (Grid Coordination)
    Note right of ChargerDevice: Space Robotics (Laser Comm)
    Note right of ChargerDevice: Hospital Equipment (UWB Comm)

4. Integration with Emerging Tech

Enabling Description:

• AI-Orchestrated Adaptive Charging Network: A central AI platform, utilizing deep reinforcement learning, manages an entire network of charging devices and numerous batteries. This AI receives aggregated overvoltage monitoring results from all batteries (transmitted during their individual pause cycles) and environmental data from charging devices. It dynamically adjusts the intermittent charging schedules, power levels, and even prioritizes certain devices based on global network demand, predicted battery degradation, and energy grid conditions, optimizing overall battery lifespan and energy efficiency.
• Decentralized Autonomous Charging (DAC) with DLT: The charging set operates as an autonomous entity on a Distributed Ledger Technology (DLT) network. The battery's overvoltage monitoring unit securely hashes and signs its monitoring results. During the intermittent communication window, this signed data is transmitted to the charging device, which also signs it and adds it as a transaction to a DLT. This DLT transaction triggers smart contracts to adjust charging power (ensuring compliance and preventing overcharge) and to settle micro-payments for energy consumed, creating a trustless and auditable charging ecosystem.
• Quantum-Secured Feedback Channel: The wireless communication link between the overvoltage monitoring unit and the charging power adjusting unit (during the intermittent pauses) is secured using quantum key distribution (QKD). Entangled photon pairs or weak coherent pulses are used to establish a provably secure encryption key, ensuring that the overvoltage feedback signals and control commands cannot be intercepted or tampered with by an eavesdropper, critical for highly sensitive applications like military or medical device charging.

graph TD
    A[Battery Overvoltage Monitor] --> B{Wireless Transmit (QKD)};
    B --> C[Charging Device Adjuster (QKD)];
    C -- AI Orchestrator --> D[Network Management];
    C -- DLT Transaction --> E[Blockchain/DLT Network];
    D -- Adjust Parameters --> F[High Freq Power Driver];
    E --> G[Automated Payment/Auditing];

5. The "Inverse" or Failure Mode

Enabling Description:

• Tiered Fault Tolerance with Redundant Communication: The charging set implements multiple redundant communication channels for overvoltage feedback. The primary channel (e.g., 10-15 MHz inductive communication) is supplemented by a secondary channel (e.g., a low-power Wi-Fi direct link) and a tertiary channel (e.g., optical flashing via an LED/photodiode pair). If the primary link fails to transmit or receive during a pause, the system automatically attempts communication over the secondary, then tertiary, ensuring critical overvoltage alerts always reach the charger, preventing catastrophic failure.
• Adaptive "Limp Home" Charging: If the overvoltage monitoring unit detects a persistent but non-critical overvoltage or an unresolvable communication error, the battery requests a "limp home" charging profile. The charging device then reduces its output power significantly (e.g., to 10% of nominal) and applies only constant voltage mode charging, signaling a "maintenance required" alert to the user. This allows partial charging to prevent complete battery depletion while waiting for service, avoiding full shutdown.
• Predictive Shutdown Protocol: An AI model within the charging set (distributed between battery and charger) continuously analyzes charging history, internal diagnostic data, and overvoltage events. If the AI predicts a high probability of imminent, unmanageable overvoltage or battery failure (e.g., within 5 subsequent charge cycles), the system initiates a controlled, preemptive shutdown of all charging operations for that specific battery, sends a "critical maintenance" alert to a central system, preventing unexpected failures and enabling proactive replacement.

stateDiagram-v2
    [*] --> Idle
    Idle --> Charging: Start_Charge
    Charging --> MonitorFeedback: Periodic_Comm_Pause
    MonitorFeedback --> NormalCharge: Feedback_OK
    MonitorFeedback --> CommunicationFail: No_Feedback
    CommunicationFail --> RedundantComm: Try_Secondary_Channel
    RedundantComm --> Charging: Success_Revert_Normal
    RedundantComm --> AdaptiveLimpHome: All_Comm_Fail_or_Persistent_Overvoltage
    AdaptiveLimpHome --> MaintenanceAlert: Reduced_Charge_Warning
    AdaptiveLimpHome --> [*]: User_Intervention_or_Failure
    MonitorFeedback --> PredictedFailure: AI_Predicts_Imminent_Failure
    PredictedFailure --> PredictiveShutdown: Initiate_Preemptive_Shutdown
    PredictiveShutdown --> [*]: Critical_Maintenance_Required
    NormalCharge --> Idle: Charge_Complete

Derivatives of Claim 23: Method for Controlling Charging

Claim 23 describes a method for controlling contact-less battery charging, including intermittent AC application, magnetic flux linkage, rectification, CV/CC charging, monitoring and transmitting results during pauses, and adjusting power.

1. Material & Component Substitution (Method Implications)

Enabling Description:
The method for controlling charging is implemented using advanced components. Step (a) of intermittently applying high-frequency AC current involves a digitally controlled resonant converter with GaN-based switches for precise, rapid pulse generation (e.g., 500 kHz switching frequency). For step (b), linking magnetic flux is enhanced by geometrically optimized 3D-printed ceramic coils in both primary and secondary units. Step (e) for monitoring voltages utilizes a high-resolution (16-bit) analog-to-digital converter (ADC) and a dedicated digital signal processor (DSP) for real-time Fourier analysis of voltage ripple, transmitting a compressed wavelet transform of the monitoring result via a software-defined radio (SDR) during communication pauses. Step (f) of adjusting power employs a closed-loop control algorithm executed on an FPGA, dynamically modulating the duty cycle and frequency of the primary coil's AC current with microsecond precision.

flowchart TD
    A[Intermittent AC Application (GaN Switches)] --> B[Magnetic Flux Linkage (3D Printed Coils)];
    B --> C[Rectify AC to DC];
    C --> D[Apply DC to Battery (CV/CC)];
    D --> E[Monitor Voltages (16-bit ADC, DSP)];
    E -- Transmit Compressed Wavelet (SDR) --> F[Receive Monitoring Result];
    F --> G[Adjust Primary AC Power (FPGA, Dynamic Modulation)];

2. Operational Parameter Expansion (Method Implications)

Enabling Description:

• Ultra-Fast Charging Cycles: The method is optimized for extremely rapid charging. Step (a) involves applying AC current in bursts of 100 µs duration at 1 MHz, with pause regions (step e) of only 10 µs. Monitoring and transmission (step e) must be completed within this 10 µs window, requiring ultra-low latency wireless protocols (e.g., custom UWB pulses) and dedicated hardware for real-time voltage comparison. Step (f) involves instantaneous power adjustments within microseconds to achieve "charge in seconds" scenarios.
• Deep Cycle Maintenance & Diagnostics: The method is extended for long-term battery health management. Step (a) includes charging phases lasting several minutes, followed by extended pause regions (step e) of 1-5 seconds. During these longer pauses, step (e) involves transmitting not just overvoltage status, but also detailed battery impedance spectroscopy data, temperature profiles, and historical degradation metrics, enabling proactive battery conditioning and life extension through step (f)'s adaptive power profiles.
• Adaptive Spatial Power Delivery: Step (a) is refined to involve an array of smaller primary coils. The method dynamically determines which specific primary coils to activate and at what power levels, based on real-time spatial positioning of the battery and feedback from (e) indicating optimal coupling points and localized overvoltage conditions. Step (f) then adjusts not only total power but also the spatial distribution of the magnetic field, optimizing charging for moving or misaligned batteries.

sequenceDiagram
    Charger->>+Battery: Apply_AC_Pulse (100us, 1MHz)
    Battery->>Battery: Induced_AC
    Battery->>Battery: Rectify_DC_Charge_Cell
    Battery->>+Battery: Monitor_CV_CC_Voltage
    Battery-->>-Charger: Transmit_Result (10us Pause, UWB)
    Charger->>Charger: Adjust_Primary_AC_Power (µs Response)
    Note over Charger,Battery: Ultra-Fast Charging Cycle
    Charger->>+Battery: Apply_AC_Long (Minutes)
    Battery->>Battery: Induced_AC
    Battery->>Battery: Rectify_DC_Charge_Cell
    Battery->>+Battery: Monitor_CV_CC_Voltage_Detailed
    Battery-->>-Charger: Transmit_Diagnostics (1-5s Pause)
    Charger->>Charger: Adjust_Primary_AC_Power_Adaptive
    Note over Charger,Battery: Deep Cycle Diagnostics

3. Cross-Domain Application (Method Implications)

Enabling Description:

• Distributed Environmental Sensor Network: For agricultural or environmental monitoring, the method is applied to a fleet of low-power IoT sensors. Step (a) involves a mobile drone or robotic vehicle intermittently flying/driving over sensor fields, broadcasting inductive power. In step (e), individual sensors monitor their internal power converters for overvoltage and transmit concise "power request" or "overcharge warning" signals via a mesh radio network (e.g., Zigbee) during the pauses. Step (f) allows the drone to adjust its power output or even alter its flight path to optimize charging for specific sensors.
• Robotic Fleet Management in Warehouses: For charging autonomous mobile robots (AMRs) in a warehouse. Step (a) involves strategically placed floor-embedded charging pads intermittently activating. In step (e), each AMR monitors its battery health and transmits overvoltage/charge status to a central fleet management system via enterprise Wi-Fi during brief, scheduled charging pauses. Step (f) allows the fleet manager to dynamically adjust charging power per pad, prioritize robots with low charge, or direct overcharged robots to a lower-power pad.
• Smart Grid Ancillary Services with EVs: Electric vehicles (EVs) integrated into a smart grid for vehicle-to-grid (V2G) services. Step (a) sees grid-connected inductive chargers intermittently providing power. Step (e) involves the EV's advanced Battery Management System (BMS) monitoring cell-level voltages and reporting aggregate overvoltage status and grid-service readiness to the grid operator via ISO 15118 protocol during charging pauses. Step (f) enables the grid operator to dynamically adjust charging/discharging power across a fleet of EVs to balance grid load or provide frequency regulation.

flowchart TD
    A[Charging Device Applies AC (Intermittent)] --> B[Battery Receives Induced AC];
    B --> C[Rectify & Charge Battery];
    C --> D[Monitor Overvoltage (During Pause)];
    D -- Wireless Comm --> E[Charging Device Receives Result];
    E --> F[Adjust AC Power];
    subgraph Context
        G[Drone/Robot Patrol (Ag/Robotics)] --> A;
        H[EV BMS (Smart Grid)] --> D;
        I[Fleet/Grid Management] --> F;
    end

4. Integration with Emerging Tech (Method Implications)

Enabling Description:

• AI-Enhanced Predictive Control Method: Prior to step (a), an AI model analyzes historical charging data, battery characteristics, and real-time environmental factors to predict optimal intermittent AC application patterns, including pulse width and frequency, to preemptively avoid overvoltage. In step (e), the monitoring result is fed back to this AI, which then refines its predictive model in real-time, enabling step (f) to make proactive power adjustments that optimize battery lifespan and charging speed, rather than merely reacting to detected overvoltage.
• IoT-Contextualized Charging Method: Step (e) is expanded to include the collection of data from integrated IoT sensors (e.g., device skin temperature, ambient humidity, user presence via proximity sensor) alongside overvoltage monitoring. This contextual data is transmitted to the charging device. Step (f) then uses this combined information to adjust the primary AC power more intelligently; for instance, reducing power if the device's skin temperature is high, regardless of direct overvoltage.
• Blockchain-Verified Charging Protocol: The execution of each stage of the charging method (a) through (f) is cryptographically timestamped and recorded. Step (e) includes the generation of a hashed and signed monitoring result by the battery's secure element. This signed result is transmitted and verified by the charger. Step (f) then includes recording the power adjustment command and the new charging parameters as a transaction on a permissioned blockchain, creating an immutable, verifiable audit trail for every charging interaction, ensuring protocol compliance and facilitating transparent energy accounting.

sequenceDiagram
    ChargerAI->>Charger: Predict_Optimal_Pattern
    Charger->>Battery: Intermittent_AC (a,b)
    Battery->>Battery: Rectify_Charge (c,d)
    Battery->>Battery: Monitor_OV_and_IoT_Data (e)
    Battery->>Charger: Transmit_Result_to_AI (e)
    ChargerAI->>Charger: Refine_Model_and_Adjust_Power (f)
    Charger->>Blockchain: Record_Charging_Tx

5. The "Inverse" or Failure Mode (Method Implications)

Enabling Description:

• Safety-Critical Disconnect Protocol: If step (e) detects a catastrophic overvoltage condition (e.g., cell rupture risk), the method immediately bypasses step (f). Instead, the battery sends an emergency "hard-disconnect" command. The charging device executes a safety-critical physical disconnect by de-energizing the primary coil and opening a high-current circuit breaker, ensuring complete power cessation faster than any gradual adjustment, preventing thermal runaway or fire.
• Degraded Mode Operation for Communication Loss: If wireless communication for step (e) fails persistently during pause periods (e.g., 3 consecutive failures), the method triggers a degraded operation mode. Step (f) involves the charging device automatically reverting to a predefined, ultra-conservative, low-power charging profile (e.g., a constant voltage trickle charge at 5V, 100mA). This ensures minimal power is still supplied without feedback, preventing damage, while continuously attempting to re-establish the communication link.
• Self-Correction with Local Power Capping: If step (e) detects a minor, transient overvoltage that is within safe, but undesirable, limits, the method employs a localized self-correction. Step (f) on the battery side (prior to transmitting feedback) involves the battery's microprocessor temporarily reducing the current draw from the CV/CC supplier by briefly increasing its internal impedance, allowing the charger to continue its cycle while the battery locally mitigates the transient, only transmitting a "minor adjustment made" status if the condition persists.

stateDiagram-v2
    state "Charging (Steps a-d)" as Charging
    state "Monitor & Transmit (e)" as MonitorTransmit
    state "Adjust Power (f)" as AdjustPower
    state "Emergency Disconnect" as EmergencyDisconnect
    state "Degraded Mode" as DegradedMode
    state "Self-Correcting Cap" as SelfCorrectingCap

    [*] --> Charging
    Charging --> MonitorTransmit: After_Charge_Burst
    MonitorTransmit --> AdjustPower: Feedback_Received_OK
    AdjustPower --> Charging: Continue_Charging
    MonitorTransmit --> EmergencyDisconnect: Catastrophic_Overvoltage
    EmergencyDisconnect --> [*]: Hard_Disconnect_Triggered
    MonitorTransmit --> DegradedMode: Persistent_Comm_Failure
    DegradedMode --> Charging: Comm_Reestablished
    MonitorTransmit --> SelfCorrectingCap: Minor_Transient_Overvoltage
    SelfCorrectingCap --> MonitorTransmit: Local_Correction_Applied
    DegradedMode --> [*]: Final_Failure

---

Combination Prior Art Scenarios

These scenarios combine the inventive concepts of US Patent 8013568 with existing open-source standards, demonstrating how the patent's core functionalities could be integrated into common technological frameworks.

1. US8013568 + Qi Wireless Power Standard (WPC) + MQTT (Message Queuing Telemetry Transport)

Description:
A wireless charging system built upon the widely adopted Qi wireless power transfer standard (developed by the Wireless Power Consortium, WPC) for basic inductive power transfer and low-level device identification. The advanced overvoltage monitoring and wireless feedback mechanism, as taught in US8013568, are integrated into this Qi framework. Specifically, during the Qi standard's defined "ping" or "negotiation" phases (which inherently involve intermittent power pulses), the battery's overvoltage monitoring unit transmits its monitoring result. This transmission uses a low-bandwidth, encrypted MQTT over a Bluetooth Low Energy (BLE) link, leveraging the existing BLE communication capabilities often found in Qi-compatible devices. The MQTT messages containing overvoltage status and adjustment requests are then interpreted by the Qi-enabled charging device, which uses this feedback to modify its output power according to US8013568's principles.

Prior Art Value: This combination demonstrates that extending existing, ubiquitous wireless charging standards like Qi with enhanced safety features (overvoltage feedback and dynamic power adjustment) via standard IoT communication protocols (MQTT over BLE) is an obvious architectural improvement. It preempts claims on adaptive charging layered over established inductive power platforms.

2. US8013568 + Open Charge Point Protocol (OCPP) + Modbus (Industrial Automation Protocol)

Description:
An industrial-scale electric vehicle (EV) charging infrastructure employs the inductive power transfer principles of US8013568. The charging device (charger station) communicates with a central charging network management system (e.g., cloud-based or local server) using the Open Charge Point Protocol (OCPP) for functionalities such as starting/stopping charging sessions, billing, and status reporting. Internally, the high-frequency power driving unit within the charging device communicates with the magnetic field generating unit and power conversion modules using Modbus TCP/IP for robust industrial control. The intermittent wireless overvoltage feedback from the EV's Battery Management System (BMS), which integrates the battery-side overvoltage monitoring logic of US8013568, is transmitted to the charging device. This feedback is then either encapsulated as a custom data payload within an OCPP "StatusNotification" or "MeterValues" message, or communicated directly over a dedicated Modbus TCP/IP link during the intermittent power pauses. The charging power adjusting unit within the charger uses this received data to dynamically adjust charging power via Modbus commands to its internal power driving unit.

Prior Art Value: This scenario highlights the obvious integration of US8013568's adaptive charging technology into high-power, networked industrial applications using prevalent open standards. It shows that the core feedback mechanism is not limited to consumer electronics but is readily adaptable to complex, managed charging environments, leveraging existing communication protocols for control and data exchange.

3. US8013568 + Bluetooth Low Energy (BLE) Generic Attribute Profile (GATT) + JSON (JavaScript Object Notation)

Description:
A compact, personal wireless charging set (e.g., for earbuds, smartwatches, or portable medical sensors) utilizes the intermittent inductive charging and overvoltage feedback mechanism of US8013568. The wireless communication between the battery's overvoltage monitoring unit and the charging device's power adjusting unit is implemented using Bluetooth Low Energy (BLE) and its Generic Attribute Profile (GATT). During the intermittent power pauses, the battery's wireless transmitting unit sends its monitoring result (e.g., voltage difference, overvoltage flag, battery temperature) as a JSON-formatted string, published as a GATT characteristic notification to the charging device. The charging device, upon receiving this JSON payload, parses the data and adjusts the high-frequency AC current accordingly. This BLE link can also allow a smartphone application to display real-time charging status and battery health.

Prior Art Value: This combination demonstrates that the specific wireless feedback mechanism of US8013568 can be readily implemented using ubiquitous, low-power short-range wireless communication standards like BLE and common data formats like JSON, making it an obvious choice for consumer and small-device applications. This preempts claims on using standard, efficient wireless protocols for transmitting monitoring data in an intermittent, adaptive charging system.