Patent 9914365

Derivative works

Defensive disclosure: derivative variations of each claim designed to render future incremental improvements obvious or non-novel.

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Derivative works

Defensive disclosure: derivative variations of each claim designed to render future incremental improvements obvious or non-novel.

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Defensive Disclosure: US Patent 9914365 Derivatives

This document outlines potential derivative works and technical disclosures related to US Patent 9914365, "Apparatus and method for rapid charging using shared power electronics." The objective is to establish prior art for various incremental improvements, thereby rendering them obvious or non-novel for future competitive advancements. This disclosure avoids summarizing the existing patent and focuses solely on novel variations.


Derivatives of Independent Claim 1 (Apparatus)

Independent Claim 1 describes an apparatus comprising a first energy storage device, a first voltage converter (bi-directional), and a first controller communicating with a second remote controller to enable a second charging voltage for rapid charging.

Derivative 1.1: GaN-based Ultra-High Frequency Bidirectional Converter

Enabling Description:
This apparatus utilizes a first voltage converter constructed with Gallium Nitride (GaN) high-electron-mobility transistors (HEMTs) in a multi-level topology (e.g., flying capacitor multilevel inverter or cascaded H-bridge) for significantly increased switching frequencies (e.g., 200 kHz to 1 MHz) compared to conventional silicon IGBTs. This allows for a drastic reduction in the size and weight of associated passive components (inductors, capacitors), leading to higher power density and efficiency. The first controller implements advanced control algorithms (e.g., space vector modulation with adaptive switching frequency control) specifically optimized for GaN device characteristics to minimize switching losses and manage thermal dissipation, enabling the first voltage converter to achieve 98% efficiency during both motoring and rapid charging modes. Communication with the second controller is optimized for high-bandwidth, low-latency data exchange to synchronize the GaN-based converter's output with the second charging voltage, ensuring seamless power aggregation on the DC bus. The first energy storage device is a solid-state battery (SSB) with enhanced power density and cycle life, leveraging fast charging capabilities.

graph TD
    A[First Energy Storage Device (SSB)] --> B(DC Bus)
    B -- High-Freq DC --> C{First Voltage Converter (GaN Multilevel Inverter)}
    C -- High-Freq AC --> D[Electromechanical Device]
    E[Remote Power Supply] -- AC --> F(AC-DC Rectifier)
    F -- DC --> B
    G[First Controller] -- Control --> C
    G -- Data --> H[Second Controller (Remote)]
    H -- Control --> I[Second Voltage Converter (Remote)]
    I -- DC --> B
    subgraph Rapid Charging
        F --> B
        I --> B
    end
    style C fill:#f9f,stroke:#333,stroke-width:2px
    style G fill:#ccf,stroke:#333,stroke-width:2px
    style H fill:#ccf,stroke:#333,stroke-width:2px

Derivative 1.2: Cryogenically Cooled Superconducting Energy Storage System

Enabling Description:
This apparatus integrates a high-temperature superconducting (HTS) magnetic energy storage (SMES) coil as the first energy storage device, operating at cryogenic temperatures (e.g., 77K using liquid nitrogen) to achieve extremely high power density and near-unity efficiency during charge/discharge cycles. The first voltage converter is a specialized cryo-compatible DC-DC converter, utilizing SiC MOSFETs designed for operation within or adjacent to the cryogenic environment, minimizing thermal transfer. This converter handles megawatt-scale power flows with minimal resistive losses. The electromechanical device is a direct-drive superconducting motor. The first controller employs predictive thermal management algorithms to optimize the SMES coil's temperature and charge rate, coordinating with the second controller for the provision of the second charging voltage. The combined power allows for charging rates of >5C for large-scale industrial or grid-support applications.

graph TD
    A[HTS SMES (77K)] --> B(Cryo-Compatible DC Bus)
    B -- MW DC --> C{Cryo SiC DC-DC Converter}
    C -- Control --> D[Superconducting Motor]
    E[First Controller] -- Predictive Thermal Mgmt --> C
    E -- Sync Control --> F[Second Controller (Remote)]
    F -- Power Provision --> G[Second Remote Power Supply]
    G -- Augmented DC --> B
    subgraph Rapid Charging
        C --> B
        G --> B
    end
    style A fill:#afe,stroke:#333,stroke-width:2px
    style C fill:#f9f,stroke:#333,stroke-width:2px

Derivative 1.3: Marine Vessel Shore-to-Ship Rapid Charging System

Enabling Description:
This apparatus is designed for electric marine vessels (e.g., ferries, tugboats). The first energy storage device is a large-scale marine-grade battery pack (e.g., 2 MWh LiFePO4). The first voltage converter is the vessel's propulsion inverter, rated for multi-megawatt AC motor drive for marine thrusters. When the vessel is docked, the first controller (on-board ship) communicates with a shore-side second controller (at the charging station). This shore-side controller orchestrates the transfer of a second charging voltage from a dedicated shore power converter and potentially from the propulsion inverters of other docked or connected vessels (acting as remote energy conversion systems) via a shared shore DC bus. This combined power flow enables rapid charging of the marine vessel's battery, reducing port turnaround times. The connection system uses high-current, liquid-cooled plugs compliant with maritime standards.

graph TD
    subgraph Electric Marine Vessel
        A[Marine Battery Pack] --> B(Vessel DC Bus)
        B -- Propulsion DC --> C{Vessel Propulsion Inverter}
        C -- AC --> D[Marine Thruster Motor]
        E[Vessel Controller] -- Control --> C
        E -- Communication (IEC 61892) --> F[Shore-Side Controller]
    end
    subgraph Charging Station (Shore)
        G[Shore Power Grid] -- AC --> H[Dedicated Shore Converter]
        H -- DC --> I(Shared Shore DC Bus)
        J[Other Docked Vessels' Inverters] -- DC --> I
        F -- Control --> H
        F -- Control --> J
        I -- High-Power DC Link --> B
    end
    E -- Request Charge --> F
    F -- Coordinate --> E
    H & J --> I
    I --> B

Derivative 1.4: AI-Optimized Adaptive Charging Network (ACN) with Swarm Intelligence

Enabling Description:
This apparatus features an AI-driven first controller on-board the vehicle, which continuously monitors the first energy storage device's state (SoC, SoH, temperature, internal resistance) and predicts optimal charging profiles using deep learning models. This controller communicates with a second remote controller, which is part of a distributed charging network employing swarm intelligence. The second controller coordinates multiple adjacent energy conversion systems (e.g., other vehicles' inverters, stationary battery storage, local solar PV) to collectively supply the second charging voltage. The AI algorithms optimize power allocation in real-time, considering battery degradation models, grid load balancing, localized energy prices, and individual vehicle charging priorities. Charging currents are dynamically adjusted across multiple parallel paths to maximize charging speed while extending battery lifespan and minimizing local grid impact. Data is exchanged securely with cryptographic protocols.

graph TD
    subgraph Vehicle (First Apparatus)
        A[First Energy Storage Device] --> B(Vehicle DC Bus)
        B -- DC --> C{First Voltage Converter}
        C -- AC --> D[Electromechanical Device]
        E[First Controller (AI Agent)] -- Control --> C
        E -- Data (Secured Protocol) --> F[Shared DC Bus Controller (AI Orchestrator)]
        A -- Telemetry (IoT Sensors) --> E
    end
    subgraph Adaptive Charging Network
        F -- Optimization Commands --> G[Remote Energy Conversion System 1]
        F -- Optimization Commands --> H[Remote Energy Conversion System 2]
        F -- Optimization Commands --> I[...]
        G -- DC --> J(Shared DC Bus)
        H -- DC --> J
        I -- DC --> J
        J -- Aggregated DC --> B
        F -- Grid/Renewable Data --> K[Grid Management System]
        K -- Power Flow --> G
        K -- Power Flow --> H
        K -- Power Flow --> I
    end
    E --> F
    J --> B

Derivative 1.5: Passive Power-Sharing System with Thermal Dissipation Management

Enabling Description:
This apparatus operates in a low-power, limited-functionality mode or a safe-fail condition where the rapid charging capability is temporarily suspended or reduced. In this scenario, the first controller detects an anomaly (e.g., elevated internal temperature of the first voltage converter, partial failure of an inverter leg, or degraded insulation resistance). Instead of relying on active boosting from the first voltage converter and external sources, the system defaults to a direct, current-limited rectification of the remote power supply. The second charging voltage from the second remote power supply is provided as a lower, trickle-charge current via passive current-sharing resistors or inductors on the shared DC bus, rather than actively controlled boosting. This "limp-home" or "maintenance charge" mode prevents further damage to components while ensuring a minimal energy transfer. The first controller monitors a set of critical fault parameters and broadcasts a reduced capability status to the second controller, which then adjusts its output to a safe, pre-defined low-power profile.

stateDiagram-v2
    [*] --> Idle
    Idle --> Connected: Plug-in
    Connected --> Charging_Request: User Selects Mode
    Charging_Request --> Rapid_Charging: Normal Operation
    Rapid_Charging --> Fault_Detected: Component Over-temp / Fault
    Fault_Detected --> Safe_Mode_Charging: Degraded Operation
    Safe_Mode_Charging --> Charging_Complete: Low Power Charge Complete
    Rapid_Charging --> Charging_Complete: Normal Charge Complete
    Charging_Complete --> Disconnected: Unplug
    Disconnected --> Idle
    Safe_Mode_Charging --> Emergency_Shutdown: Critical Failure
    Emergency_Shutdown --> [*]

    state Rapid_Charging {
        Rapid_Charging: High Power, Coordinated
        Rapid_Charging --> Monitor_Thermal_Load
        Monitor_Thermal_Load --> Fault_Detected: Thermal Exceeded
    }
    state Safe_Mode_Charging {
        Safe_Mode_Charging: Low Power, Passive Sharing
        Safe_Mode_Charging --> Current_Limit_Engaged
    }

Derivatives of Independent Claim 2 (Method)

Independent Claim 2 describes a method for rapid charging, involving coupling a first energy storage device to a first voltage converter, configuring a first controller to use the first voltage converter for a first charging voltage, and configuring the first controller to cause a second charging voltage from a second remote power supply to be provided for rapid charging.

Derivative 2.1: Method for Interoperable Multi-Standard Charging Protocol Negotiation

Enabling Description:
This method enhances the rapid charging process by dynamically negotiating charging parameters between the first controller (on-board vehicle) and the second controller (charging station) using an extended communication protocol that supports multiple charging standards (e.g., CCS, CHAdeMO, GB/T, Tesla Supercharger). The method involves an initial handshake where the first controller advertises its supported protocols and maximum charging capabilities (voltage, current, power) for both its internal converter and for receiving external power. The second controller then analyzes this information, along with the availability and capabilities of connected remote power supplies, the current grid conditions, and the vehicle's requested charging speed. It then selects the optimal charging standard and power distribution strategy, instructing the first voltage converter and the second remote power supply to establish the first and second charging voltages according to the agreed-upon profile. This allows for universal rapid charging without requiring dedicated hardware for each standard on the vehicle.

sequenceDiagram
    participant VC as Vehicle Controller (First Controller)
    participant CS as Charging Station Controller (Second Controller)
    participant RP1 as Remote Power Supply 1
    participant RP2 as Remote Power Supply 2

    VC->CS: Initiate_Charging_Request (Desired_Mode: Rapid, Supported_Protocols: [CCS, CHAdeMO], Max_Onboard_Power: X kW)
    CS->VC: Acknowledge_Request (Available_Protocols: [CCS], Available_Power_Sources: [RP1, RP2])
    CS->CS: Evaluate_Charging_Strategy (based on vehicle capabilities, grid, energy price, RP availability)
    CS->VC: Negotiate_Charging_Profile (Protocol: CCS, Target_Voltage: Y V, Target_Current: Z A, Split: {Onboard: Z1 A, RP1: Z2 A, RP2: Z3 A})
    VC->CS: Accept_Charging_Profile
    CS->RP1: Command_Set_Output (Voltage: Y V, Current: Z2 A)
    CS->RP2: Command_Set_Output (Voltage: Y V, Current: Z3 A)
    VC->VC: Configure_Onboard_Converter (to generate Z1 A at Y V)
    CS->VC: Close_Contactor_Shared_DC_Bus
    VC-->VC: Monitor_Battery_Status
    VC->CS: Send_Status_Updates (SoC, Temp, Health)
    CS->CS: Dynamically_Adjust_Power (if needed)
    CS->VC: Send_Adjustment_Commands
    Note over VC,CS: Rapid Charging in Progress
    VC->CS: Charging_Complete / Stop_Request
    CS->RP1: Command_Disable_Output
    CS->RP2: Command_Disable_Output
    CS->VC: Open_Contactor_Shared_DC_Bus

Derivative 2.2: Thermal-Aware Adaptive Charging Method for Battery Longevity

Enabling Description:
This method focuses on optimizing battery health during rapid charging. The first controller integrates a sophisticated battery thermal model and state-of-health (SoH) estimator. During rapid charging, the first controller continuously monitors individual battery cell temperatures, internal impedance, and degradation indicators. It uses this data to predict potential thermal runaway or accelerated aging. This information is then communicated to the second controller, which dynamically adjusts the magnitude and duty cycle of the first and second charging voltages. For instance, if a battery hot spot is detected, the second controller might reduce the current from the second remote power supply and request the first controller to lower its contribution, or even implement a pulsed charging strategy with integrated cooling cycles. This adaptive method prioritizes battery longevity over peak charging speed when thermal limits are approached, extending the overall useful life of the energy storage device.

flowchart TD
    A[Vehicle Controller (First Controller)] -- Monitor --> B{Battery Pack (Temp, SoH)}
    B -- Data --> A
    A -- Predict Thermal Risk --> C{Thermal Model / SoH Estimator}
    C -- Risk Level / Recommended Action --> D[Charging Station Controller (Second Controller)]
    D -- Adjust Commands --> E[First Voltage Converter (Vehicle)]
    D -- Adjust Commands --> F[Second Remote Power Supply]
    E -- First Charging Voltage --> G[Energy Storage Device]
    F -- Second Charging Voltage --> G
    subgraph Adaptive Charging Loop
        A -- (Pulsed Current/Voltage) --> G
        D -- (Reduced Power) --> G
    end

Derivative 2.3: Blockchain-Validated Peer-to-Peer (P2P) Energy Sharing

Enabling Description:
This method describes a P2P energy sharing model for rapid charging within a localized network of electric vehicles (EVs). The first controller of the charging EV initiates a request for rapid charging, broadcasting its energy needs and desired price per kilowatt-hour onto a localized blockchain network. The second controllers of other connected EVs with surplus energy and bi-directional charging capabilities (acting as "second remote power supplies") detect this request. They then autonomously offer to contribute a second charging voltage, specifying their available power and asking price. Smart contracts on the blockchain validate these offers, mediate the energy transaction, and securely record the energy transfer and payment. The second controller of the charging station facilitates the physical power flow via shared DC buses but the financial transaction and trust verification are handled by the distributed ledger, ensuring transparency and enabling dynamic pricing models based on local supply and demand among vehicles.

sequenceDiagram
    participant EV_A as Charging EV (First Controller)
    participant EV_B as Supplying EV (Second Controller 1)
    participant EV_C as Supplying EV (Second Controller 2)
    participant CS as Charging Station (Central Node)
    participant BC as Blockchain Network

    EV_A->BC: Request_Charge (kW, Price_Bid)
    EV_B->BC: Offer_Energy (kW_avail, Price_Ask)
    EV_C->BC: Offer_Energy (kW_avail, Price_Ask)
    BC->EV_A: Validate_Offers (from EV_B, EV_C)
    EV_A->BC: Select_Offers (e.g., EV_B)
    BC->EV_B: Initiate_Smart_Contract
    CS->CS: Establish_Physical_Connection (EV_A, EV_B)
    CS->EV_B: Command_Begin_Power_Export
    CS->EV_A: Command_Begin_Power_Import
    Note over EV_A,EV_B: Energy Transfer in Progress
    EV_B->CS: Monitor_Export_Telemetry
    EV_A->CS: Monitor_Import_Telemetry
    CS->BC: Record_Transaction_Data (Energy_Transferred, Duration)
    BC->EV_A: Deduct_Funds
    BC->EV_B: Distribute_Payment
    EV_A->BC: Confirm_Transaction

Derivative 2.4: Integrated Hydrogen Fuel Cell Assisted Charging

Enabling Description:
This method involves coupling a first energy storage device (e.g., Li-ion battery) to a first voltage converter, where the first controller is configured to cause the first voltage converter to provide a first charging voltage. Additionally, the second remote power supply is a modular hydrogen fuel cell system. The method configures the first controller to communicate with a second controller integrated into the fuel cell system. This second controller manages the fuel cell's power output, converting the fuel cell's DC output into a second charging voltage. This second charging voltage is then combined with the first charging voltage from the vehicle's onboard converter to rapidly charge the first energy storage device. The system can dynamically adjust the power contribution from the fuel cell based on hydrogen availability, load demand, and grid conditions, providing a localized, emission-free augmentation to the charging process.

graph TD
    A[Vehicle Energy Storage Device] --> B(Vehicle DC Bus)
    B -- DC --> C{Vehicle Voltage Converter}
    C -- AC --> D[Motor]
    E[Vehicle Controller] -- Control --> C
    E -- Comm --> F[Fuel Cell Controller (Second Controller)]
    subgraph Fuel Cell System
        G[Hydrogen Tank] --> H[Fuel Cell Stack]
        H -- DC Power --> I{Fuel Cell DC-DC Converter}
        I -- DC --> J(Shared DC Voltage Bus)
    end
    J --> B
    E & F -- Coordinated Power Delivery --> B

Derivative 2.5: Demand-Response Optimized Charging using Predictive Analytics

Enabling Description:
This method leverages predictive analytics for rapid charging within a smart grid context. The first controller collects usage patterns, planned travel routes, and desired departure times from the vehicle's owner. This data, along with the current state of the first energy storage device, is transmitted to the second controller at the charging station. The second controller processes this data using predictive algorithms that forecast future energy demand, local renewable energy generation, and real-time electricity pricing. It then dynamically schedules and adjusts the delivery of the first and second charging voltages. For example, it might initiate a rapid charge during periods of low grid demand or high renewable availability (e.g., midday solar peak), even if the immediate need for rapid charging isn't critical, to optimize energy costs and grid stability. Conversely, if grid stress is high, it might suggest a delayed or slower charge. This method balances rapid charging needs with grid sustainability and economic efficiency.

sequenceDiagram
    participant VC as Vehicle Controller (First Controller)
    participant CS as Charging Station Controller (Second Controller)
participant G as Smart Grid
    VC->CS: Upload_Usage_Data (Route, Departure, SoC)
    CS->G: Request_Grid_Status (Demand, Renewables, Price)
    G->CS: Provide_Grid_Data
    CS->CS: Run_Predictive_Analytics (Optimal_Charging_Window, Power_Target)
    CS->VC: Suggest_Charging_Plan (Start_Time, Duration, Power_Level)
    VC->CS: Accept_Plan / Override_Request
    alt If Plan Accepted
        CS->CS: Prepare_Charging_Resources (First_VC, Second_PS)
        CS->VC: Initiate_Coordinated_Charge (Power_Profile)
        VC->VC: Control_First_VC
        CS->CS: Control_Second_PS
        Note over VC,CS: Rapid Charging (Adaptive)
    else If Override Requested
        CS->CS: Adjust_Plan_Instantly (Max_Available_Power_Now)
        CS->VC: Initiate_Coordinated_Charge (Immediate_High_Power)
        VC->VC: Control_First_VC
        CS->CS: Control_Second_PS
        Note over VC,CS: Rapid Charging (Immediate)
    end

Derivatives of Independent Claim 3 (System)

Independent Claim 3 describes a system with a first power bus, a second power bus, a first vehicle (with its energy storage device, motor, voltage converter, and first controller), and a first energy conversion system (remote from the vehicle, with a second voltage converter and second controller) providing a second charging voltage for rapid charging.

Derivative 3.1: Distributed Network of Mobile Energy Storage (Power Banks on Wheels)

Enabling Description:
This system envisions a network where the "first energy conversion system" is not a stationary charging station, but another electric vehicle specifically configured as a mobile energy storage unit (MESU) or "power bank on wheels." These MESUs are equipped with large-capacity energy storage devices and robust bi-directional voltage converters optimized for both vehicle propulsion and high-power energy transfer. The second power bus is a standardized high-voltage DC coupling port on the MESU. The MESU's second controller communicates with the first vehicle's controller via a wireless mesh network (e.g., IEEE 802.11s) and orchestrates the delivery of the second charging voltage. The MESU can draw power from the first power bus (utility grid) at opportunistic times to charge its own battery, then deploy to locations needing rapid vehicle charging, effectively decentralizing the charging infrastructure.

graph LR
    subgraph Grid Infrastructure
        A[First Power Bus (Utility Grid)]
    end
    subgraph Mobile Energy Storage Unit (MESU)
        B[MESU Energy Storage] -- DC --> C{MESU Voltage Converter}
        C -- AC --> D[MESU Motor]
        E[MESU Controller (Second Controller)] -- Control --> C
        C -- DC --> F(Second Power Bus - DC Coupling Port)
        E -- Wireless Mesh (802.11s) --> G[First Vehicle Controller]
        A -- AC Charge --> C
    end
    subgraph First Vehicle
        G[First Vehicle Controller] -- Control --> H{First Vehicle Voltage Converter}
        H -- AC --> I[First Vehicle Motor]
        H -- DC --> J[First Vehicle Energy Storage]
        F -- High-Power DC Link --> J
    end
    E -- Coordinate Power Transfer --> G
    C -- Rapid Charge --> J

Derivative 3.2: Industrial Fleet Management Charging System

Enabling Description:
This system is deployed in an industrial setting for charging a fleet of electric material handling equipment (e.g., forklifts, automated guided vehicles (AGVs)). The first vehicle (e.g., a forklift) comprises its traction battery (first energy storage device), drive motor, and onboard DC-DC converter (first voltage converter) suitable for its voltage range (e.g., 48V-96V). The first power bus is the facility's localized DC microgrid. The first energy conversion system is a centralized charging hub, comprising a large DC-DC converter (second voltage converter) drawing power from the facility's main AC supply or a dedicated DC bus. The second controller at the charging hub dynamically dispatches charging slots and power levels based on operational schedules, real-time battery status of the forklifts, and shift changes, ensuring maximum fleet uptime. The second power bus is a robust, quick-connect DC interface in each charging bay.

flowchart TD
    A[Facility AC Supply] --> B{AC-DC Rectifier}
    B -- DC --> C(Facility DC Microgrid)
    subgraph Central Charging Hub (First Energy Conversion System)
        C -- DC --> D{Central DC-DC Converter (Second Voltage Converter)}
        D -- DC --> E(Shared DC Power Bus - Charging Bays)
        F[Hub Controller (Second Controller)] -- Control --> D
        F -- Schedule/Monitor --> G[Fleet Management System]
    end
    subgraph Electric Forklift (First Vehicle)
        E -- Quick-Connect DC --> H{Onboard DC-DC Converter (First Voltage Converter)}
        H -- DC --> I[Forklift Battery (First Energy Storage)]
        H -- DC --> J[Forklift Motor]
        K[Forklift Controller (First Controller)] -- Control --> H
        K -- Report Status --> F
    end
    G -- Optimize Fleet --> F
    F -- Commands --> K
    D -- Rapid Charge --> I

Derivative 3.3: Dynamic Voltage Bus for Extreme Fast Charging (XFC)

Enabling Description:
This system implements a dynamic, multi-voltage shared DC bus as the second power bus. Instead of a fixed DC voltage, the second remote power supply (first energy conversion system) and the vehicle's onboard converter are capable of operating across a wide output voltage range (e.g., 400V to 1500V). The second controller dynamically adjusts the voltage of the second power bus to match the optimal charging voltage profile required by the first energy storage device, which might change during different phases of charging (e.g., constant current phase at lower voltage, constant voltage phase at higher voltage). This reduces conversion losses and allows for higher power transfer by minimizing current for a given power level. The communication protocol between the first and second controllers includes real-time voltage synchronization commands to prevent current surges or mismatches when combining the first and second charging voltages. The first power bus is a high-voltage AC utility connection.

graph TD
    A[First Power Bus (High-Voltage AC Grid)] -- AC --> B{Rectifier/PFC}
    B -- DC --> C(HV DC Link)
    subgraph Remote Energy Conversion System
        C -- DC --> D{Second Voltage Converter (Bidirectional, Wide-Range DC-DC)}
        D -- Dynamic DC --> E(Dynamic Shared DC Power Bus)
        F[Second Controller] -- Control --> D
        F -- Voltage Sync --> G[First Vehicle Controller]
    end
    subgraph First Vehicle
        H{First Voltage Converter (Bidirectional, Wide-Range DC-DC)} -- Dynamic DC --> E
        H -- DC --> I[First Energy Storage Device]
        H -- AC --> J[First Motor]
        G[First Vehicle Controller] -- Control --> H
        G -- Request Profile --> F
    end
    F -- Optimal Voltage Setpoint --> E
    D & H -- Dynamic Voltage & Current --> I

Derivative 3.4: Predictive Maintenance with Digital Twin Integration

Enabling Description:
This system incorporates a digital twin of both the first vehicle's power electronic energy conversion system and the remote energy conversion system. IoT sensors embedded in all critical components (IGBTs, GaN FETs, inductors, capacitors, battery cells) continuously stream operational data (temperature, voltage, current, vibration) to the respective controllers. These controllers (first and second) feed the data to a cloud-based digital twin platform. The digital twin uses machine learning models to simulate component degradation, predict potential failures (e.g., capacitor aging, IGBT bond wire lift-off, battery thermal runaway), and recommend proactive maintenance or adjustments to charging parameters. For example, if the digital twin predicts reduced lifespan for a specific vehicle's battery under current rapid charging conditions, the second controller might autonomously reduce the combined charging power or suggest a specific charging profile to the operator to mitigate degradation.

classDiagram
    class First_Vehicle_System {
        +FirstEnergyStorageDevice
        +FirstVoltageConverter
        +FirstController
        +IoTSensors: List<SensorData>
    }
    class Remote_Conversion_System {
        +SecondVoltageConverter
        +SecondController
        +IoTSensors: List<SensorData>
    }
    class Cloud_Digital_Twin_Platform {
        +DigitalTwinModel: ML_Model
        +PredictiveMaintenanceEngine
        +DataHistorian
    }
    class Charging_Optimization_Engine {
        +ML_Algorithms
        +ChargingProfileGenerator
    }

    First_Vehicle_System "1" --> "1..*" IoTSensors: streams data
    Remote_Conversion_System "1" --> "1..*" IoTSensors: streams data
    IoTSensors --> Cloud_Digital_Twin_Platform: real-time data
    Cloud_Digital_Twin_Platform --> PredictiveMaintenanceEngine: provides insights
    First_Vehicle_System --> FirstController
    Remote_Conversion_System --> SecondController
    FirstController --> Cloud_Digital_Twin_Platform: aggregates data
    SecondController --> Cloud_Digital_Twin_Platform: aggregates data
    PredictiveMaintenanceEngine --> Charging_Optimization_Engine: suggests adjustments
    Charging_Optimization_Engine --> FirstController: sends optimized commands
    Charging_Optimization_Engine --> SecondController: sends optimized commands

Derivative 3.5: Hybrid Power Train Sharing for Energy Resiliency

Enabling Description:
This system extends the concept of shared power electronics to include vehicles with hybrid powertrains (e.g., plug-in hybrids or range-extended EVs). The "first vehicle" could be a purely electric vehicle, while the "first energy conversion system" (remotely located) is a hybrid electric vehicle (HEV). The HEV's internal combustion engine and generator (part of its propulsion system) function as a flexible "second remote power supply." When the HEV is connected to the charging station and is not actively driving, its engine can operate at its optimal efficiency point to generate electrical power via its onboard generator and voltage converter. This generated power is then converted by the HEV's bi-directional inverter (second voltage converter) and delivered as a second charging voltage to the first vehicle's energy storage device via the shared DC power bus. This allows for rapid charging in locations with limited grid infrastructure or during grid outages, leveraging the HEV as a mobile generator and power bank.

graph TD
    subgraph First Vehicle (Pure EV)
        A[EV Battery] --> B(EV DC Bus)
        B -- DC --> C{EV Inverter/Converter}
        C -- AC --> D[EV Motor]
        E[EV Controller] -- Control --> C
        F[Shared DC Power Bus] --> B
    end
    subgraph Charging Station
        G[Grid Power] -- AC --> H{AC-DC Charger}
        H -- DC --> F
    end
    subgraph First Energy Conversion System (HEV)
        I[Gasoline Tank] --> J[Internal Combustion Engine (ICE)]
        J --> K[Generator]
        K -- AC --> L{HEV Inverter/Converter (Second Voltage Converter)}
        L -- DC --> M[HEV DC Bus]
        M --> N[HEV Battery]
        O[HEV Controller (Second Controller)] -- Control --> L
        M -- DC --> F
    end
    O -- Coordinate Power Contribution --> E
    E -- Request Power --> O
    L -- DC Charge --> B
    H -- DC Charge --> B

Combination Prior Art Scenarios

Here are three scenarios combining the concepts of US Patent 9914365 with existing open-source standards to create prior art.

Scenario 1: OCPP-Enabled Dynamic Shared Charging with Load Balancing

Enabling Description:
An electric vehicle charging system that implements the principles of US9914365 (shared power electronics for rapid charging) and is fully compliant with the Open Charge Point Protocol (OCPP), specifically OCPP 2.0.1. The first controller (vehicle-side) communicates with the second controller (charging station) using OCPP messages for detailed charging profile negotiation, real-time status updates (State of Charge, battery health parameters), and fault reporting. The second controller leverages OCPP's Smart Charging profiles and Schedule Charging functionality to orchestrate the power contribution from both the vehicle's onboard converter (first charging voltage) and the remote energy conversion systems (second charging voltage). This orchestration is dynamically adjusted to perform load balancing across the charging station and optimize grid interaction, considering the station's total available power and individual vehicle charging demands, as specified in OCPP's local smart charging features.

sequenceDiagram
    participant EV as Electric Vehicle (First Controller)
    participant CP as Charge Point (Second Controller)
    participant CSMS as Central System Management Server
    participant RPS as Remote Power Supply
    EV->CP: BootNotification.req (OCPP)
    CP->CSMS: BootNotification.req (OCPP)
    CP->EV: Authorize.req (OCPP)
    EV->CP: StartTransaction.req (OCPP)
    CP->CSMS: StatusNotification.req (OCPP)
    EV->CP: MeterValues.req (SoC, Temp, Power)
    CP->CSMS: MeterValues.req (Aggregated Data)
    CP->CP: Negotiate_Shared_Charging (US9914365 logic)
    CP->RPS: Command_Set_Output (Voltage, Current)
    EV->EV: Configure_Onboard_Converter (First Charging Voltage)
    RPS->EV: Deliver_Second_Charging_Voltage
    EV->EV: Combine_Power_for_Rapid_Charge
    CP->CSMS: Send_Composite_Charging_Profile (OCPP Smart Charging)
    CP->CP: Dynamic_Load_Balancing (OCPP)
    Note over EV,CP: Rapid Charging Active
    EV->CP: StopTransaction.req (OCPP)
    CP->CSMS: StopTransaction.req (OCPP)
    RPS->CP: Report_Status
    CP->RPS: Command_Disable_Output

Scenario 2: ISO 15118 Compliant Bidirectional Shared Charging

Enabling Description:
A vehicle-to-grid (V2G) enabled charging system where electric vehicles can rapidly charge from an external supply and other vehicles, fully compliant with ISO 15118 (Road vehicles - Vehicle to grid communication interface). The first vehicle's first controller and the charging station's second controller utilize the ISO 15118 communication protocol, specifically focusing on the advanced charging schedules and bi-directional power transfer capabilities (Extended V2G Message) within the standard. This allows for not only the vehicle to communicate its charging needs and battery parameters but also to inform the second controller about its capability to provide power (acting as a remote energy conversion system for another vehicle) or accept complex charging profiles from shared sources. The second power bus facilitates DC energy transfer, adhering to ISO 15118's DC charging communication messages for dynamic power management and grid interaction within the shared charging ecosystem.

sequenceDiagram
    participant EV as Electric Vehicle (First Controller)
    participant EVSE as Charging Station (Second Controller)
    participant GV as Guest Vehicle (Another EV sharing power)
    EV->EVSE: SessionSetupReq (ISO 15118)
    EVSE->EV: SessionSetupRes (ISO 15118)
    EV->EVSE: ServiceDiscoveryReq (ISO 15118, with BPT support)
    EVSE->EV: ServiceDiscoveryRes (ISO 15118)
    EV->EVSE: ServiceDetailReq (ISO 15118, DC charging)
    EVSE->EV: ServiceDetailRes (ISO 15118)
    EV->EVSE: PaymentServiceSelectionReq (ISO 15118)
    EVSE->EV: PaymentServiceSelectionRes (ISO 15118)
    EV->EVSE: ChargeParameterDiscoveryReq (ISO 15118, desired charging power, battery status)
    EVSE->EV: ChargeParameterDiscoveryRes (ISO 15118, proposed charging limits)
    EVSE->GV: Check_Power_Availability (internal communication)
    GV->EVSE: Announce_Power_Offer (kW)
    EVSE->EV: PowerDeliveryReq (ISO 15118, target power from EVSE + GV)
    EV->EV: Control_Onboard_Converter
    GV->GV: Activate_Bi-directional_Export
    Note over EV,EVSE: Rapid Charging via Shared DC Bus (ISO 15118)
    EV->EVSE: MeteringReceiptReq (ISO 15118)
    EVSE->EV: MeteringReceiptRes (ISO 15118)
    EV->EVSE: PowerDeliveryReq (ISO 15118, Stop Charging)
    EVSE->EV: PowerDeliveryRes (ISO 15118)

Scenario 3: OpenADR Integrated Grid-Responsive Shared Charging

Enabling Description:
A rapid charging system that actively participates in demand-response programs, integrating with the Open Automated Demand Response (OpenADR) 2.0b standard. The charging station's second controller acts as a Virtual End Node (VEN) in an OpenADR network, receiving price signals, demand-response events, and grid constraints from a central Virtual Top Node (VTN) (e.g., utility or independent system operator). The second controller uses these signals to intelligently manage the aggregate power draw for rapid charging. During peak demand or high electricity prices, the second controller might reduce the total combined charging power (from both the vehicle's onboard converter and remote energy conversion systems) or temporarily defer non-critical rapid charge sessions, while still guaranteeing a baseline charge. Conversely, during periods of surplus renewable energy, the system could initiate accelerated rapid charging using maximum available shared power, all in response to OpenADR signals.

graph TD
    A[Utility/ISO (VTN - OpenADR)] --> B{OpenADR Server}
    B -- OpenADR Signals (Price, DR Events) --> C[Charging Station Controller (VEN - Second Controller)]
    C -- Control --> D[Remote Energy Conversion System]
    C -- Control --> E[First Vehicle Controller]
    E -- Control --> F{First Voltage Converter}
    D -- DC Power --> G(Shared DC Power Bus)
    F -- DC Power --> G
    G --> H[First Energy Storage Device (Vehicle)]
    C -- Monitor & Report --> H
    C -- Adjust Charging Strategy (US9914365) --> G

Generated 6/2/2026, 6:04:54 PM