Portable device for releasing and receiving charge from multiple entities

Abstract

A system is described. The system comprises one or more adapters; a first entity; a second entity; and a host intelligent charging receiver. The host smart charge receiver includes a processor storing instructions in non-transitory memory that, when executed, cause the processor to: determine a presence of an adapter electrically coupled to the host vehicle; identifying at least one of a first entity and a second entity electrically coupled to the host vehicle through the adapter; establishing a connection between the host vehicle, the first entity, and the second entity; transmitting a command to one of the first entity and the second entity to function as an extended charger based on the received first and second charges; and providing optimal charging for the first battery pack of the host vehicle by providing at least one of the first charging and the second charging.

Description

Technical Field

[0001] The present disclosure generally relates to the field of charging electric vehicles. More specifically, the present disclosure relates to releasing and receiving charging from multiple entities. Background Art

[0002] Suppose a vehicle is stranded for a long time due to weather or traffic. The problem is that when one or more vehicles lose power or the power drops below a safe level, there is no way to combine resources to power a vehicle. Therefore, it would be great to receive power from multiple resources (e.g., other vehicles in a similar situation) until the situation changes. For example, if a vehicle loses power, the operator can request help from other nearby vehicles. However, when all vehicles are below the discharge threshold (e.g., a preset charging level to ensure there is enough remaining charge to perform the required operations without stranding the vehicle), it may be impossible or insufficient to receive charging from one vehicle. Additionally, if a vehicle is stranded, it may be difficult for a vehicle with discharging capabilities to reach the vehicle in need. Therefore, a system should be provided that can receive charging from multiple resources through a resource chain.

[0003] Therefore, there has long been a need for a system and method for releasing and receiving charging from multiple entities. Summary of the Invention

[0004] The following paragraphs provide a summary to provide a basic understanding of one or more embodiments described herein. This summary is not intended to identify key or critical elements or to define any scope of different embodiments and / or any scope of the claims. The sole purpose of the summary is to present some concepts in a simplified form as a prelude to a more detailed description herein.

[0005] In one or more embodiments described herein, systems, devices, computer - implemented methods, methods, apparatuses, and / or computer program products are presented that facilitate releasing and receiving charging from multiple entities.

[0006] In one aspect, a system is described. The system includes one or more adapters; a first entity; a second entity; and a host intelligent charging receiver. The host intelligent charging receiver includes a processor that stores instructions in a non-transitory memory, and when the instructions are executed, the processor will perform the following operations: determine the presence of one or more adapters electrically coupled to the host vehicle; identify at least one of the first entity and the second entity electrically coupled to the host vehicle through one or more adapters; establish a connection between the host vehicle, the first entity, and the second entity; based on a first charge and a second charge received from the first entity and the second entity respectively, transmit a command to one of the first entity and the second entity to act as an extended charger; and provide optimal charging for one or more first battery packs of the host vehicle by providing at least one of the first charge and the second charge.

[0007] In one aspect, a method is described. The method includes: determining the presence of one or more adapters electrically coupled to the host vehicle; identifying at least one of the first entity and the second entity electrically coupled to the host vehicle through one or more adapters; establishing a connection between the host vehicle, the first entity, and the second entity; based on a first charge and a second charge received from the first entity and the second entity respectively, transmitting a command to one of the first entity and the second entity to act as an extended charger; and providing optimal charging for one or more first battery packs of the host vehicle by providing at least one of the first charge and the second charge.

[0008] In one aspect, a non-transitory computer-readable storage medium is described. The non-transitory computer-readable storage medium includes a series of instructions that, when executed by a processor, cause: determining the presence of one or more adapters electrically coupled to the host vehicle; identifying at least one of the first entity and the second entity electrically coupled to the host vehicle through one or more adapters; establishing a connection between the host vehicle, the first entity, and the second entity; based on a first charge and a second charge received from the first entity and the second entity respectively, transmitting a command to one of the first entity and the second entity to act as an extended charger; and providing optimal charging for one or more first battery packs of the host vehicle by providing at least one of the first charge and the second charge.

[0009] The methods and systems disclosed herein can be implemented in any manner to achieve various aspects and can be executed in the form of a non-transitory machine-readable medium that contains a set of instructions that, when executed by a machine, cause the machine to perform any operation disclosed herein. Other features will become apparent from the drawings and the subsequent detailed description. Description of the Drawings

[0010] These aspects and other aspects of the present disclosure will now be described in more detail with reference to the accompanying drawings showing exemplary embodiments, wherein:

[0011] Figure 1 Show a system according to one or more embodiments.

[0012] Figure 2 Show a method according to one or more embodiments.

[0013] Figure 3 Show a non-transitory computer-readable storage medium according to one or more embodiments.

[0014] Figure 4 Show a block diagram of a system according to one or more embodiments.

[0015] Figure 5 Show a battery pack of a host vehicle including individual batteries according to one or more embodiments.

[0016] Figure 6 Show a battery pack of a host vehicle including multiple batteries according to one or more embodiments.

[0017] Figure 7 Schematically show a battery pack including a battery and a battery management system according to one or more embodiments.

[0018] Figure 8 Show a message sent from a host intelligent charging receiver to a first entity according to one or more embodiments.

[0019] Figure 9 Show a message sent from a host intelligent charging receiver to a first entity according to one or more embodiments.

[0020] Figure 10 View depicting an embodiment where the main adapter has more outlets relative to the power extension cord.

[0021] Figure 11 Show power transfer between a host vehicle, a first entity, and a second entity according to one or more embodiments.

[0022] Figure 12 Show power transfer between a host vehicle, a first entity, and a second entity according to one or more embodiments.

[0023] Figure 13 Show power transfer between a host vehicle, a first entity, and a second entity according to one or more embodiments.

[0024] Figure 14 Show a system according to one or more embodiments.

[0025] Figure 15 Displays a method according to one or more embodiments.

[0026] Figure 16 Displays a non - transient computer - readable medium according to one or more embodiments.

[0027] Figure 17 Displays a message sent from a host intelligent charging receiver to a first entity according to one or more embodiments.

[0028] Figure 18 Displays a message sent from a host intelligent charging receiver to a first entity according to one or more embodiments.

[0029] Figure 19 Displays a first entity acting as an extended charger according to one or more embodiments.

[0030] Figure 20 Displays a first entity acting as an extended charger according to one or more embodiments.

[0031] Figure 21 Displays a first entity acting as an extended charger according to one or more embodiments.

[0032] Figure 22A Shows a block diagram of a network security module in terms of systems and servers.

[0033] Figure 22B Shows an embodiment of a network security module.

[0034] Figure 22C Shows another embodiment of a network security module.

[0035] Figure 23A Shows the structure of a neural network / machine - learning model with a feedback loop.

[0036] Figure 23B Shows the structure of a neural network / machine - learning model with reinforcement learning.

[0037] According to the accompanying drawings and the following detailed description, other features of this embodiment will become apparent. Detailed Description

[0038] For simplicity and clarity of illustration, the drawings show the general manner of construction. The description and the drawings may omit the description and details of well - known features and techniques to avoid unnecessarily obscuring the present disclosure. The drawings exaggerate the dimensions of some elements relative to other elements to help improve the understanding of the embodiments of the present disclosure. The same reference numerals in different drawings denote the same elements.

[0039] Although the detailed description herein contains many details for illustrative purposes, those of ordinary skill in the art will understand that many variations and changes to the details are contemplated herein.

[0040] Accordingly, the embodiments herein are not intended to be limiting in any generality, nor do they impose any limitations on any claims. The terms used herein are for the purpose of describing particular embodiments only and are not limiting. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure pertains.

[0041] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art.

[0042] As used herein, the articles "a" and "an" refer to one or more than one (i.e., at least one) of the grammatical objects of the article. For example, "an element" refers to one element or more than one element. Further, unless otherwise stated or the context clearly indicates a singular form, the use of the articles "a" and "an" in this specification and the drawings shall be construed as "one or more".

[0043] As used herein, the terms "example" and / or "exemplary" are meant to be used as an example, instance, or illustration. To avoid doubt, such examples do not limit the subject matter described herein. Further, any aspect or design described herein as "example" and / or "exemplary" is not necessarily superior or better than other aspects or designs, nor does it exclude equivalent exemplary structures and techniques known to those of ordinary skill in the art.

[0044] As used herein, the terms "first", "second", "third", etc. (if any) in the specification and claims are used to distinguish similar elements and do not necessarily describe a particular order or temporal order. These terms may be interchanged where appropriate, e.g., the embodiments herein are capable of operating in an order other than the order shown or otherwise described herein. Further, the terms "comprising", "having" and any variations thereof cover non-exclusive inclusion, so a process, method, system, article, device or apparatus that comprises a list of elements is not necessarily limited to those elements, but may include other elements not expressly listed or inherent to such process, method, system, article, device or apparatus.

[0045] As used herein, the terms "left", "right", "front", "rear", "top", "bottom", "above", "below", etc. (if any) in the specification and claims are for descriptive purposes only and do not necessarily describe a permanent relative position. Where appropriate, the terms so used may be interchanged, such that embodiments of the devices, methods and / or articles described herein, for example, are capable of operating in an orientation different from that shown or otherwise described herein.

[0046] Unless expressly stated, any element, action, or instruction used herein is not critical or essential. Additionally, the term "set" includes items (e.g., related items, unrelated items, combinations of related and unrelated items, etc.) and may be interchangeable with "one or more". If only one item is referred to, the term "a" or similar language is used. Additionally, terms such as "has", "have", "owns", etc. are open-ended terms. Additionally, the phrase "based on" means "at least partially based on" unless otherwise expressly stated.

[0047] As used herein, the terms "system", "device", "unit", and / or "module" refer to different components, component parts, or levels of components of an order. However, these terms may be replaced by other expressions that achieve the same purpose.

[0048] As used herein, the terms "coupled", "coupled", "coupled (singular)", "coupling", etc. refer to connecting two or more elements mechanically, electrically, and / or in other ways. Two or more electrical elements may be electrically coupled together but not mechanically or in other ways. Coupling can be for any length of time, such as permanent, semi-permanent, or only transient. "Electrical coupling" includes all types of electrical coupling. The absence of words such as "detachable", "removable", etc. near words such as "coupled" does not mean that the coupling being discussed is or is not detachable.

[0049] As used herein, the term "or" means inclusive "or" rather than exclusive "or". That is, unless otherwise stated or the context clearly indicates. "X employs A or B" represents any natural inclusive arrangement. That is, if X employs A; X employs B; or X employs both A and B, then "X employs A or B" is satisfied in any of the above cases.

[0050] As used herein, two or more elements or modules are "integral" or "integrated" if they operate functionally together. Two or more elements are "non-integral" if each element can operate functionally independently.

[0051] As used herein, the term "real-time" refers to an operation that occurs as soon as possible after a triggering event occurs. The triggering event may include receiving data required to perform a task or otherwise process information. Due to the inherent delays in transmission and / or computing speed, the term "real-time" encompasses operations that are "near" real-time or slightly delayed from the triggering event. In many embodiments, "real-time" may represent real-time minus the time delay for processing (e.g., determining) and / or transmitting data. The specific time delay may vary depending on the type and / or quantity of data, the processing speed of the hardware, the transmission capacity of the communication hardware, the transmission distance, etc. However, in many embodiments, the time delay may be less than about one second, two seconds, five seconds, or ten seconds.

[0052] As used herein, the term "about" can mean within a specified or unspecified range of the specified or unspecified value. In some embodiments, "about" can mean within plus or minus ten percent of the specified value. In other embodiments, "about" can mean within plus or minus five percent of the specified value. In further embodiments, "about" can mean within plus or minus three percent of the specified value. In still other embodiments, "about" can mean within plus or minus one percent of the specified value.

[0053] Digital electronic circuits, or computer software, firmware, or hardware, including the structures disclosed in this specification and their structural equivalents, or combinations of one or more of them, can implement the implementations and all functional operations described in this specification. The implementation can be one or more computer program products, that is, one or more computer program instruction modules, which are encoded on a computer-readable medium for a data processing device to execute or control the operation of the data processing device. The computer-readable medium can be a machine-readable storage device, a machine-readable storage substrate, a memory device, a composition of matter affecting a machine-readable propagated signal, or combinations of one or more of them. The term "computing system" encompasses all devices, apparatuses, and machines for processing data, such as programmable processors, computers, or multiple processors or computers. In addition to the hardware, the device can also include code that creates an execution environment for the computer programs under discussion, such as code constituting processor firmware, a protocol stack, a database management system, an operating system, or combinations of one or more of them. A propagated signal is an artificially generated signal (e.g., an electrical, optical, or electromagnetic signal generated by a machine) that encodes information for transmission to a suitable receiving device.

[0054] The actual special control hardware or software code for implementing these systems and / or methods is not limited to these implementations. Thus, any software and any hardware can implement these systems and / or methods based on the description herein without reference to specific software code.

[0055] A computer program (also known as a program, software, software application, script, or code) is written in any suitable form of programming language, including compiled or interpreted languages. A computer program can be deployed on any suitable form of computer, including a stand-alone program or modules, components, subroutines, or other units suitable for a computing environment. A computer program does not necessarily correspond to a file in a file system. The program can be stored in a part of a file that holds other programs or data (e.g., one or more scripts stored in a markup language document), in a single file dedicated to the relevant program, or in multiple coordinated files (e.g., files that store one or more modules, subroutines, or portions of code). A computer program can be executed on one computer or on multiple computers located at one site or distributed across multiple sites and interconnected by a communication network.

[0056] One or more programmable processors execute one or more computer programs to perform functions by operating on input data and generating output, performing the processes and logical flows described in this specification. The processes and logical flows can also be performed by dedicated logic circuitry, and the apparatus can also be implemented as dedicated logic circuitry, such as, but not limited to, a field-programmable gate array (FPGA), an application-specific integrated circuit (ASIC), an application-specific standard product (ASSP), a system-on-a-chip (SOC) system, a complex programmable logic device (CPLD), etc.

[0057] Processors suitable for executing a computer program include, by way of example, both general and special purpose microprocessors, as well as one or more processors of any suitable type of digital computer. The processor will receive instructions and data from read-only memory or random access memory or both. Elements of a computer can include a processor for executing instructions and one or more memory devices for storing instructions and data. The computer will also include or be operatively coupled to receive data, transmit data, or both, to / from one or more mass storage devices for storing data (such as magnetic disks, magneto-optical disks, optical disks, or solid state disks). However, a computer need not have such devices. Additionally, another device (such as a mobile phone, a personal digital assistant (PDA), a mobile audio player, a global positioning system (GPS) receiver, etc.) can be embedded in the computer. Computer-readable media suitable for storing computer program instructions and data include all forms of non-volatile memory, media, and storage devices, such as semiconductor storage devices (e.g., erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), and flash memory devices), magnetic disks (e.g., internal hard disks or removable disks), magneto-optical disks (e.g., compact disc read-only memory (CDROM) discs, digital versatile disc read-only memory (DVD-ROM) discs), and solid state disks. Dedicated logic circuitry can supplement or integrate the processor and the memory.

[0058] For interaction with a user, a computer may have a display device, such as a cathode ray tube (CRT) or a liquid crystal display (LCD) monitor, for displaying information to the user, and a keyboard and a pointing device, such as a mouse or a trackball, by which the user can provide input to the computer. Other types of devices also provide interaction with the user. For example, feedback to the user may be any suitable form of sensory feedback, such as visual feedback, auditory feedback, or tactile feedback; and the computer may receive input from the user in any suitable form, including acoustic, speech, or tactile input.

[0059] A computing system that includes backend components (such as data servers), or includes middleware components (such as application servers), or includes frontend components (such as client computers having a graphical user interface or a web browser through which the user can interact with the implementation), or any suitable combination of one or more such backend, middleware, or frontend components, can implement the implementations described herein. Any suitable form or digital data communication medium (such as a communication network) can interconnect the components of the system. Examples of communication networks include local area networks (LANs) and wide area networks (WANs), such as intranets and the Internet.

[0060] The computing system may include a client and a server. The client and the server are located far from each other and typically interact through a communication network. The relationship between the client and the server is created by computer programs running on their respective computers and they have a client-server relationship with each other.

[0061] Embodiments may include or utilize a special-purpose or general-purpose computer including computer hardware. Embodiments within the scope of the present invention may also include physical and other computer-readable media for carrying or storing computer-executable instructions and / or data structures. Such computer-readable media can be any media accessible by a general-purpose or special-purpose computer system. A computer-readable medium storing computer-executable instructions is a physical storage medium. A computer-readable medium carrying computer-executable instructions is a transmission medium. Thus, by way of example and not limitation, embodiments of the present invention may include at least two different types of computer-readable media: physical computer-readable storage media and transmission computer-readable media.

[0062] Although the embodiments described herein are reference to specific example embodiments, it will be apparent that various modifications and changes can be made to these embodiments without departing from the broader spirit and scope of the various embodiments. For example, hardware circuits (e.g., complementary metal-oxide semiconductor (CMOS)-based logic circuits), firmware, software (e.g., embodied in a non-transitory machine-readable medium), or any combination of hardware, firmware, and software can enable and operate the various devices, units, and modules described herein. For example, transistors, logic gates, and circuits (e.g., application-specific integrated circuits (ASICs) and / or digital signal processor (DSP) circuits) can embody various electrical structures and methods.

[0063] Furthermore, non-transitory machine-readable media and / or systems can embody the various operations, processes, and methods disclosed herein. Accordingly, the specification and drawings are illustrative, not restrictive.

[0064] Physical computer-readable storage media include RAM, ROM, EEPROM, CD-ROM, or other optical disk storage (e.g., CDs, DVDs, etc.), magnetic disk storage, or other magnetic storage devices, solid state drives, or any other medium. They store the required program code in the form of computer-executable instructions or data structures, accessible by a general or special purpose computer.

[0065] As used herein, the term "network" refers to one or more data links that enable the transfer of electronic data between computer systems and / or modules and / or other electronic devices. When a network or another communication connection (whether wired, wireless, or a combination of wired or wireless) transfers or provides information to a computer, the computer properly views the connection as a transmission medium. A general or special purpose computer accesses the transmission medium, which can include a network and / or data link that carries the required program code in the form of computer-executable instructions or data structures. The scope of computer-readable media includes the combinations described above, which enable the transfer of electronic data between computer systems and / or modules and / or other electronic devices. Additionally, upon reaching various computer system components, program code in the form of computer-executable instructions or data structures can be automatically transferred from the transmission computer-readable media to a physical computer-readable storage medium (and vice versa). For example, computer-executable instructions or data structures received via a network or data link can be buffered in RAM within a network interface module (NIC) and then ultimately transferred to the computer system RAM and / or a less volatile computer-readable physical storage medium in the computer system. Thus, computer system components that also (or even primarily) use the transmission medium can include a computer-readable physical storage medium.

[0066] Computer-executable instructions include, for example, instructions and data that cause a general-purpose computer, a special-purpose computer, or a special-purpose processing device to perform a particular function or group of functions. The computer-executable instructions may be, for example, binary, intermediate format instructions (such as assembly language), or even source code. Although the subject matter described herein is in language directed to structural features and / or methodological acts, such features or acts do not limit the subject matter defined in the claims. Rather, the features and acts described herein are example forms for implementing the claims.

[0067] Although this specification contains many details, these details do not constitute a limitation on the scope of the disclosure or the claims, but rather a description of particular features of a particular implementation. A single implementation may implement some of the features described in this specification in the context of separate implementations. Conversely, multiple implementations may implement the various features described herein separately or in any suitable sub-combination in the context of a single implementation. Moreover, although the features described herein operate in certain combinations and are even initially claimed as such, in some cases, one or more features from a claimed combination may be excised from the combination, and the claimed combination may be directed to a sub-combination or a variant of a sub-combination.

[0068] Similarly, although operations are depicted in the figures herein in a particular order for achieving a desired result, it should not be understood that these operations are required to be performed in the particular order shown or in sequential order, or that all of the illustrated operations are required to achieve the desired result. In some cases, multitasking and parallel processing may be advantageous. Additionally, the separation of various system components in an implementation should not be understood to require such separation in all implementations, and it should be understood that the described program components and systems may be integrated in a single software product or packaged into multiple software products.

[0069] Although particular combinations of features are recited in the claims and / or particular combinations of features are disclosed in the specification, these combinations are not intended to limit the disclosure that may be implemented. Other implementations are also within the scope of the claims. For example, the acts recited in the claims may be performed in a different order and still achieve the desired result. In fact, many of these features may be combined in ways not explicitly recited in the claims and / or not disclosed in the specification. Although each dependent claim may directly depend on only one claim, the disclosure that may be implemented includes the combination of each dependent claim with all the other claims in the claim set.

[0070] A computer system (such as a computer memory) may implement these methods. Specifically, one or more processors execute computer-executable instructions stored in the computer memory to perform various functions (such as the acts described in the embodiments).

[0071] Those skilled in the art will recognize that the present invention can be implemented in a network computing environment having a variety of types of computer system configurations, including personal computers, desktop computers, laptop computers, messaging processors, handheld devices, multiprocessor systems, microprocessor-based or programmable consumer electronics, network PCs, minicomputers, mainframe computers, mobile phones, PDAs, pagers, routers, switches, etc. The present invention can also be implemented in a distributed system environment where local and remote computer systems are connected by a network (either by a hardwired data link, a wireless data link, or a combination of hardwired and wireless data links) and perform tasks. In a distributed system environment, program modules can be located in both local and remote memory storage devices.

[0072] Unless otherwise noted, the following terms and phrases shall have the following meanings.

[0073] As used herein, the term "sensor module" refers to a unit that includes components or circuitry in addition to sensors. The additional components or circuitry make the sensors easier to use. A sensor module can be an integrated circuit that includes additional components and sensors suitable for an application. A sensor module can include one or more sensors that operate together functionally. For example, one or more cameras and one or more sensors within a sensor module are integrated with each other to determine charge consumption factors. The sensors within a sensor module operate in an integrated manner to monitor environmental conditions, the external environment, etc., to estimate and monitor charge consumption.

[0074] As used herein, the term "electric vehicle (EV)" refers to a vehicle for highway use as defined in 49 CFR 523.3, driven by an electric motor that draws current from an on-vehicle energy storage device (such as a battery), which can be recharged from an off-vehicle power source (such as residential or public power service or an on-vehicle fuel generator). An EV can be a two-wheeled or multi-wheeled vehicle, mainly manufactured for public streets and roads. An EV can be referred to as an electric car, electric vehicle, electric road vehicle (ERV), plug-in vehicle (PV), plug-in vehicle (xEV), etc., and xEV can be classified into plug-in all-electric vehicle (BEV), battery electric vehicle, plug-in electric vehicle (PEV), hybrid electric vehicle (HEV), hybrid plug-in electric vehicle (HPEV), plug-in hybrid electric vehicle (PHEV), etc.

[0075] As used herein, the term "plug-in electric vehicle (PEV)" refers to an electric vehicle that charges its on-vehicle main battery by connecting to an electrical grid.

[0076] The term "plug-in vehicle (PV)" refers to an electric vehicle that can be wirelessly charged through an electric vehicle supply equipment (EVSE) without the use of a physical plug or physical socket.

[0077] As used herein, the term "heavy-duty vehicle (HD vehicle)" means any four-wheeled or more-wheeled vehicle as defined in 49 CFR 523.6 or 49 CFR 37.3 (for buses).

[0078] As used herein, the term "light-duty plug-in electric vehicle" means a three-wheeled or four-wheeled vehicle driven by an electric motor that draws current from a rechargeable battery or other energy device and is primarily used on public streets, roads, and highways and has a gross vehicle weight rating of less than 4,545 kilograms.

[0079] As used herein, the term "state of health (SoH)" refers to a quality factor of a battery pack's condition compared to its ideal state. The state of health (SoH) of a battery pack describes the difference between the battery pack under study and a new battery pack and takes into account the aging of the battery cells. SoH is defined as the ratio of the maximum battery charge to its rated capacity. It can be expressed as a percentage. A battery pack can include one or more batteries.

[0080] As used herein, the term "charging station" means a device that includes at least one docking terminal with a charger for charging a battery pack. A battery pack can include one or more batteries. The term "charging station" further refers to a device that can serve as a power source for charging the battery pack of an electric vehicle, including facilitating data communication between the electric vehicle and the charging station. The communication can be established through a wired connection or a wireless connection. The charging station is also capable of charging the electric vehicle through a wired connection or a wireless connection.

[0081] As used herein, the term "host vehicle" means a vehicle that requests charging from another entity. The host vehicle can be one of an autonomous vehicle, a non-autonomous vehicle, and a semi-autonomous vehicle.

[0082] As used herein, the term "first entity" means the primary charging power source or primary charging resource applicable to charging an electric vehicle. The first entity can be an entity that has sufficient charge and can transfer the charge to another vehicle. The first entity can be the entity closest to the host vehicle. The first entity can be an entity that provides charging at a low cost or for free.

[0083] As used herein, the term "second entity" means the secondary charging power source or secondary charging resource applicable to charging an electric vehicle. The second entity can be an entity that has sufficient charge and can transfer the charge to another vehicle. The second entity can be the entity second closest to the host vehicle.

[0084] As used herein, the term "adapter" refers to a device for coupling a host vehicle to an adjacent entity. The adapter may include a device for inserting a charging cable. The adapter includes a device for coupling multiple inputs and providing a single output. By coupling more subsequent adapters, the adapter can be expanded to have more outlets / connection mechanisms. The adapter is a device for connecting a device (host vehicle) to a power source (e.g., a first entity, a second entity, etc.).

[0085] As used herein, the term "battery pack" refers to a group of any number of identical batteries or individual battery cells of a battery. The "battery pack" may also refer to a group of non-identical batteries. The batteries in the battery pack can be configured in series, parallel, or a combination of both to provide the required voltage, capacity, and / or power density.

[0086] As used herein, the term "control unit" or "control module" or "electronic control unit" refers to a functional unit in a computer system that controls one or more peripheral devices. For example, it can be a component of a charging system that provides instructions or signals to a charger unit to charge a battery pack according to charging requirements.

[0087] As used herein, the term "module" refers to any hardware, software, firmware, electronic control component, processing logic, and / or processor device, either alone or in any combination, including but not limited to: application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), electronic circuits, processors (shared, dedicated, or grouped), memories that execute one or more software or firmware programs, combinational logic circuits, and / or other suitable components that provide the said functionality.

[0088] As used herein, the term "vehicle computer system" refers to an embedded system in automotive electronics that controls one or more electrical systems or subsystems in a vehicle. The computer performs a large number of different software functions in areas such as the powertrain, chassis, driver assistance, and infotainment, and these functions are executed on separate control units. The vehicle computer system can be communicatively coupled to the user's external devices. The vehicle computer system can also be communicatively coupled to a charging station.

[0089] As used herein, the term "electronic control unit" (ECU), also known as "electronic control module" (ECM), is a system that controls one or more subsystems. The ECU can be installed in a vehicle or other motor vehicle. It can refer to a number of ECUs and can include, but is not limited to, an engine control module (ECM), a powertrain control module (PCM), a transmission control module (TCM), a brake control module (BCM) or an electronic brake control module (EBCM), a central control module (CCM), a central timing module (CTM), a general electronic module (GEM), a body control module (BCM), and a suspension control module (SCM). The ECU is sometimes collectively referred to as a vehicle computer or a vehicle central computer and can include separate computers. In one example, the electronic control unit can be embedded in vehicle electronics. In another example, the electronic control unit is wirelessly coupled to the vehicle electronics.

[0090] As used herein, the term "infotainment system" or "infotainment unit" or "in-vehicle infotainment system" (IVI) refers to a combination of systems for providing entertainment and information. In one example, the information can be delivered to the driver and passengers of the vehicle through audio / video interfaces, control elements (such as touchscreen displays, button panels, voice commands, etc.). Some of the main components of an in-vehicle infotainment system are an integrated head unit, a head-up display, a high-end digital signal processor (DSP), and a graphics processing unit (GPU) to support multiple displays, an operating system, a controller area network (CAN), low-voltage differential signaling (LVDS), and other network protocol support (as required), a connectivity module, vehicle sensor integration, a digital dashboard, etc.

[0091] As used herein, the term "charging sequence" refers to a charging mode defined by a charging system or a charging station based on battery parameters (such as state of charge, state of health) and charging time. The charging sequence can include charging levels for predefined charging time periods. The charging sequence can also include charging levels for predefined portions of the battery pack (such as healthy battery cells, degraded battery cells). The charging levels can include normal charging, fast charging, and trickle charging.

[0092] As used herein, the term "maximum charging" or "optimal charging" refers to the maximum rate at which the battery pack can be charged within a charging time without damaging the battery pack.

[0093] As used herein, the term "subsequent adapter" refers to a subsequent or additional adapter to a primary adapter. When the host vehicle requests charging from multiple entities, the subsequent adapter will be used to charge the host vehicle. The subsequent adapter can be requested and / or paired when the primary adapter has no more means to accommodate subsequent entities for charging.

[0094] As used herein, the term "host intelligent charging receiver" refers to a component that receives charging and provides charging to the host vehicle in an optimal manner. The host intelligent charging receiver includes artificial intelligence. The host intelligent charging receiver analyzes parameters related to the vehicle battery pack and determines the charging requirements of the vehicle. The host intelligent charging receiver is also adapted to analyze charging received from multiple entities and allocate the charging to the host vehicle based on at least one of charging specifications, charging requirements, and charging costs.

[0095] The term "environmental conditions" as used herein refers to the state or quality of the environment. Environmental conditions refer to various physical or specific hazards or difficulties around the host vehicle and describe the environment or conditions experienced by the host vehicle during travel.

[0096] As used herein, the term "traffic conditions" refers to a condition in transportation characterized by slower speeds, longer travel times, and increased vehicle queues. Traffic conditions may include traffic congestion, traffic jams, etc. Traffic conditions may also include information on vehicle speed, vehicle direction, and the number of vehicles facing traffic. In one embodiment, traffic conditions include real-time traffic data. In another embodiment, traffic conditions may be static or dynamic. In another embodiment, traffic conditions represent at least one of schematic, numerical, or graphical data that represents the current state of vehicles along a route at a predetermined interval. In another embodiment, traffic conditions refer to the average vehicle speed at a fixed point on a road over a period of time.

[0097] As used herein, the term "first charging" refers to charging received from a first entity.

[0098] As used herein, the term "second charging" refers to charging received from a second entity.

[0099] As used herein, the term "image analysis" refers to processing one or more images into basic components to extract meaningful information. Image analysis is a technique for obtaining information from digital images using processing tools that segment pixels in the digital image based on color or density. The segmented image is then used to quantify areas of specific features (defined by pixels).

[0100] As used herein, the term "vehicle-to-vehicle (V2V) communication" refers to a technology that allows vehicles to broadcast and receive messages. These messages may be omnidirectional messages that provide 360-degree "awareness" of other nearby vehicles. Vehicles may be equipped with appropriate software (or safety applications) that can use messages from surrounding vehicles to determine potential collision threats.

[0101] As used herein, the term "charging time" refers to the time allocated for charging. A user may provide the charging time. The charging time may also be determined by an entity or a host vehicle. The charging time may be divided into charging time periods. Each charging time period may correspond to a different charging level. Each charging time period may correspond to charging a different portion of the battery pack.

[0102] As used herein, the term "state of charge (SoC)" refers to the charging level of a battery pack relative to its capacity. The unit of SoC is percentage points (0% = empty; 100% = full). Another form of the same measurement is the depth of discharge (DoD), which is the reciprocal of SoC (100% = empty; 0% = full). SoC is typically used to discuss the current state of a battery in use, while DoD is most commonly used to discuss the battery life after repeated use.

[0103] As used herein, the term "threshold charge level" refers to the minimum charge level required for a vehicle's battery pack (having one or more batteries) to operate a predefined function of the vehicle. The threshold charge level may be preset by a processor of a control module. The threshold charge level may be changed by the processor.

[0104] As used herein, the term "two-way communication" refers to the exchange of data between two components. In one example, the first component may be a vehicle, and the second component may be an infrastructure supported by hardware, software, and firmware systems. This communication is typically wireless. In another example, the first component may be a charging system, and the second component may be a charging station.

[0105] As used herein, the term "machine learning" refers to algorithms that enable a computer to learn without being explicitly programmed, including algorithms that learn from data and make predictions. Machine learning algorithms include, but are not limited to, decision tree learning, artificial neural networks (ANNs) (also referred to herein as "neural networks"), deep learning neural networks, support vector machines, rule-based machine learning, random forests, etc. For clarity, algorithms such as linear regression or logistic regression may also be used as part of a machine learning process. However, it should be understood that using linear regression or another algorithm as part of a machine learning process is different from performing statistical analysis (such as regression) using a spreadsheet program. A machine learning process can continuously learn and adjust classifiers as new data becomes available and does not rely on explicit or rule-based programming. Statistical modeling relies on finding relationships between variables (such as mathematical equations) to predict outcomes. ANNs may have feedback loops to dynamically adjust the system output when learning from new data. In machine learning, backpropagation and feedback loops are used to train AI / ML models, thereby improving the accuracy and performance of the models over time.

[0106] As used herein, the term "communication" refers to the transmission of information and / or data from one point to another. Communication can be carried out via electromagnetic waves. It is also the flow of information from one point (referred to as the source) to another point (the receiver). Communication includes one of the following: transmitting data, instructions, and information, or a combination of data, instructions, and information. Communication occurs between any two communication systems or communication units. The term "communication" can refer to any coupling, connection, or interaction for exchanging information or data using electrical signals, using any system, hardware, software, protocol, or format, regardless of whether the exchange is carried out wirelessly or via a wired connection. The term "communication" includes systems that incorporate other more specific types of communication, such as V2I (vehicle-to-infrastructure), V2I (vehicle-to-infrastructure), V2N (vehicle-to-network), V2V (vehicle-to-vehicle), V2P (vehicle-to-pedestrian), V2D (vehicle-to-device), and V2G (vehicle-to-grid), as well as vehicle-to-everything (V2X) communication. V2X communication refers to the transmission of information from a vehicle to any entity that may affect the vehicle and vice versa. The main motivations for developing V2X are occupant safety, road safety, traffic efficiency, and energy efficiency. Depending on the underlying technology employed, there are two types of V2X communication technologies: cellular networks and other technologies that support direct device-to-device communication (such as dedicated short-range communication (DSRC), port community systems (PCS), etc.). In addition, the emergency communication device is configured on a computer with communication capabilities and communicates bidirectionally with the vehicle-mounted emergency reporting device via a radio station and a communication network (such as the public telephone network) via a communication line or via a communication satellite via satellite communication. The emergency communication device is adapted to communicate with communication terminals including the road management department, the police department, the fire department, and the hospital via a communication network. The emergency communication device can also be online-connected to the communication terminal of a relevant person or vehicle, which is associated with the occupant or vehicle and the driver or vehicle receiving the emergency reporting vehicle service.

[0107] As used herein, the term "message structure" refers to the structure of a communication message when a query and acquisition operation occurs. It includes a payload and a header, where the payload includes quantitative values of shared information and the header includes a reference to the shared information. The message structure serves as an upper-layer structure to accommodate any sub-protocol structures, such as AMQP, MQTT, Zigbee, etc.

[0108] As used herein, the term "artificial intelligence unit" refers to any system that can perceive its environment and take actions to maximize the achievement of its goals. The artificial intelligence unit utilizes a variety of machine learning algorithms to enable the system to automatically improve through experience.

[0109] As used herein, the term "communication system" or "communication module" refers to a system that enables information exchange between two points. The process of transmitting and receiving information is called communication. The main elements of communication include, but are not limited to, the information sender, the communication channel or medium, and the information receiver.

[0110] The term "Artificial Intelligence (AI)" as used herein refers to the intelligence exhibited by machines, as opposed to the natural intelligence exhibited by humans. Artificial Intelligence research is defined as any system that can perceive its environment and take actions to maximize its goals. The term "Artificial Intelligence" is now described as rational and rational action, which does not limit the expression of intelligence.

[0111] As used herein, the term "sensor module" refers to an actuator and basic control logic that acts as a regulating device, a state-directed device, or a combination operating as a single device.

[0112] As used herein, the term "charging specification" refers to a detailed description of the actual charging capacity of a vehicle. The charging specification refers to information on the basic details of charging a vehicle. The charging specification may include the actual charging mode, the actual charging duration, the actual charging sequence, the vehicle operation mode, the operation type, the charging capacity, etc.

[0113] As used herein, the term "charging requirement" refers to the charging required to complete an intended task.

[0114] As used herein, the term "merging" refers to the process of combining or joining the charging received by a first entity and a second entity together.

[0115] As used herein, the term "insertion" refers to inserting a charging cable into a host vehicle or an adapter. The charging cable may include a charger plug that perfectly matches the charging port. The charger plug may include metal pins capable of supplying power to the host vehicle to charge the battery pack.

[0116] As used herein, the term "removal" refers to removing the charging cable from the host vehicle or the adapter.

[0117] As used herein, the term "predefined charging" refers to the amount of power supplied to a host vehicle in a predefined quantity for charging the host vehicle.

[0118] As used herein, the term "predefined charging duration" is the predefined time for supplying a predefined amount of power to a vehicle to charge the vehicle.

[0119] As used herein, "itinerary" refers to the travel plan of a user / vehicle. An itinerary includes scheduled events, their locations, durations, times, dates, etc. In an embodiment, "itinerary" refers to an itinerary for going to work, an itinerary for seeing a doctor, an itinerary for going to the grocery store, etc. An itinerary can also include other less common itineraries, such as a vacation itinerary, a long-distance trip, a short trip, a quick trip, etc. An itinerary can be divided into an estimated departure time, a departure point, a start time, a destination, and an end time. An itinerary can also include intermediate waypoints that further define the route. An itinerary can include, but is not limited to, a departure point, a departure time, a destination, an expected route, and optional intermediate waypoints.

[0120] As used herein, the term "content" refers to an object, data, a visual representation, information, etc. Content may contain meaningful information. Content may also contain meaningless random information.

[0121] As used herein, the term "vehicle identification number" refers to the identification code of a specific vehicle. A vehicle identification number (VIN) is a unique code used to identify an individual motor vehicle and includes a serial number.

[0122] As used herein, the term "vehicle type" refers to the classification type of a vehicle. Vehicle types include one of an autonomous vehicle, a non-autonomous vehicle, and a semi-autonomous vehicle.

[0123] As used herein, the term "subsequent entity" refers to an entity that is located after or adjacent to the nearest entity. When the nearest entity is in trouble, the subsequent entity will be used to charge the host vehicle. The subsequent entity is the next nearest entity. When the first entity and the second entity are unavailable or have exhausted their charge, a subsequent entity can be requested and / or paired.

[0124] As used herein, the term "encryption protocol" is also referred to as a security protocol or an encryption protocol. It is an abstract or concrete protocol that performs security-related functions and generally applies encryption methods as a sequence of cryptographic primitives. The protocol describes the use of algorithms. A protocol detailed enough includes detailed information about data structures and representations to enable multiple interoperable versions of a program. Encryption protocols are widely used for secure application-level data transmission. An encryption protocol typically includes at least some of the following aspects: key negotiation or establishment, entity authentication, symmetric encryption and message authentication, secure application-level data transmission, non-repudiation methods, secret sharing methods, and secure multi-party computation. Hash algorithms can be used to verify the integrity of data. The Secure Sockets Layer (SSL) and Transport Layer Security (TLS) (the successor of SSL) are encryption protocols that can be used by network switches to protect data communication on a network.

[0125] Secure application layer data transfer widely uses cryptographic protocols. Cryptographic protocols generally include at least the following aspects: key negotiation or establishment, entity authentication, symmetric encryption and message authentication material construction, secure application layer data transfer, non-repudiation methods, secret sharing methods, and secure multi-party computation.

[0126] Network switches use encryption protocols such as Secure Sockets Layer (SSL) and Transport Layer Security (TLS) (the successor to SSL) to protect data communications over wireless networks.

[0127] As used herein, the term "unauthorized access" refers to a person using another person's account or other means to access a website, program, server, service, or other system. For example, if a person has been guessing the password or username of another person's account before obtaining access, it is considered unauthorized access.

[0128] As used herein, the term "machine learning" refers to algorithms that enable a computer to learn without being explicitly programmed, including algorithms that learn from data and make predictions. Machine learning techniques include, but are not limited to, support vector machines, artificial neural networks (ANNs) (also referred to herein as "neural networks"), deep learning neural networks, logistic regression, discriminant analysis, random forests, linear regression, rule-based machine learning, naive Bayes, nearest neighbor, decision trees, decision tree learning, and hidden Markov models, among others. For clarity, algorithms such as linear regression or logistic regression can also be used as part of a machine learning process. However, it should be understood that using linear regression or another algorithm as part of a machine learning process is different from performing statistical analysis (such as regression) using a spreadsheet program. A machine learning process can continuously learn and adjust the classifier as new data becomes available and does not rely on explicit or rule-based programming. ANNs can have feedback loops to dynamically adjust the system output when learning from new data. In machine learning, backpropagation and feedback loops are used to train AI / ML models, thereby improving the accuracy and performance of the model over time.

[0129] As used herein, the term "dashboard" is an interface for visualizing specific key performance indicators (KPIs) of a specific goal or process. It is based on data visualization and information graphics.

[0130] As used herein, "database" refers to an organized collection of information to facilitate access, management, and updating. Computer databases typically contain a collection of data records or files.

[0131] As used herein, the term "data set" (or "data collection") is a collection of data. In the case of tabular data, a data set corresponds to one or more database tables, where each column of the table represents a specific variable and each row corresponds to a given record of the associated data set. A data set lists the values of each variable for each member of the data set, such as the height and weight of an object. Each value is called data. A data set can also consist of a collection of documents or files.

[0132] As used herein, a "sensor" is a device that detects and measures a physical property of the surrounding environment and converts that information into an electrical or digital signal that can be interpreted by a person or machine for further processing. Sensors play a crucial role in collecting data for various applications in various industries. Sensors can be made of electronic, mechanical, chemical, or other engineering components. Most sensors are electronic (data is converted into electronic data), but some sensors are simpler, such as a glass thermometer, which presents visual data. Examples include sensors for measuring temperature, pressure, humidity, proximity, light, acceleration, direction, etc. In one embodiment, a sensor can be removably or fixedly mounted within a vehicle and can be arranged in various configurations to provide information to autonomous operation functions. A sensor can include one or more of a GPS unit, a radar unit, a lidar unit, an ultrasonic sensor, an infrared sensor, an inductive sensor, a camera, an accelerometer, a tachometer, a tension sensor, or a speedometer. Some sensors (such as radar, lidar, or camera units) can actively or passively scan the interior of the vehicle to detect the presence of occupants (such as children, adults, infants, passengers, drivers, etc.) to determine the occupant weight and the vehicle weight.

[0133] As used herein, a "vehicle" refers to a vehicle used for transporting people or goods. Examples of vehicles include cars, trucks, buses, etc.

[0134] The term "electronic control unit" (ECU), also known as "electronic control module" (ECM), is generally a module that controls one or more subsystems. Here, an ECU can be installed in a vehicle or other motor vehicle. It can refer to many ECUs and can include, but is not limited to, an engine control module (ECM), a powertrain control module (PCM), a transmission control module (TCM), a brake control module (BCM) or an electronic brake control module (EBCM), a central control module (CCM), a central timing module (CTM), a general electronic module (GEM), a body control module (BCM), and a suspension control module (SCM). ECUs are sometimes collectively referred to as vehicle computers or vehicle central computers and can include separate computers. In one example, an electronic control unit can be an embedded system in vehicle electronics. In another example, an electronic control unit is wirelessly coupled to vehicle electronics.

[0135] The terms "non-transitory computer-readable medium" and "computer-readable medium" include a single medium or multiple media, such as a centralized or distributed database, and / or associated caches and servers that store one or more sets of instructions. Additionally, the terms "non-transitory computer-readable medium" and "computer-readable medium" include any tangible medium that is capable of storing, encoding, or carrying a set of instructions for execution by a processor, such that, when executed, cause the system to perform any one or more of the methods or operations disclosed herein. As used herein, the term "computer-readable medium" is expressly defined to include any type of computer-readable storage device and / or storage disk, and does not include propagated signals.

[0136] As used herein, the term "vehicle data bus" refers to an interface of a vehicle data bus (such as CAN, LIN, Ethernet / IP, FlexRay, and MOST), which enables communication between on-board equipment (OBE) and other vehicle systems to support connected vehicle applications.

[0137] The term "handshake" refers to the exchange of predetermined signals between agents connected via a communication channel to ensure that they are connected to each other (as opposed to an imposter). This may also include the operator using passwords and codes. The handshake signals are transmitted back and forth over the communication network to establish a valid connection between the two sites. Hardware handshakes use dedicated lines, such as the Request to Send (RTS) and Clear to Send (CTS) lines in RS-232 serial transmissions. Software handshakes send codes such as "Synchronize" (SYN) and "Acknowledgment" (ACK) in TCP / IP transmissions.

[0138] As used herein, the term "infotainment system" or "in-vehicle infotainment system" (IVI) refers to a combination of vehicle systems used to provide entertainment and information. In one example, the information can be delivered to the driver and passengers / occupants of the vehicle through audio / video interfaces, control elements (such as touchscreen displays, button panels, voice commands, etc.). Some of the main components of an in-vehicle infotainment system are an integrated head unit, a head-up display, a high-end digital signal processor (DSP), and a graphics processing unit (GPU) to support multiple displays, an operating system, Controller Area Network (CAN), Low-Voltage Differential Signaling (LVDS), and other network protocol support (as required), a connectivity module, vehicle sensor integration, a digital dashboard, etc.

[0139] As used herein, the term "autonomous mode" refers to a mode of vehicle operation that is independent and unsupervised.

[0140] As used herein, the term "autonomous communication" includes communication over a period of time with minimal supervision in different scenarios, not being completely or fully based on precoded scenarios or precoded rules or predefined protocols. Autonomous communication is typically carried out in an independent and unsupervised manner. In one embodiment, the communication module is enabled to perform autonomous communication.

[0141] As used herein, the term "communication protocol" refers to standardized communication between any two systems. An example of a communication protocol is the DSRC protocol. The DSRC protocol uses a specific frequency band (e.g., 5.9 GHz) and specific message formats (e.g., basic safety messages, signal phase and timing, and roadside alerts) to enable communication between vehicle and infrastructure components (e.g., traffic signals and roadside sensors). DSRC is a standardized protocol whose specifications are maintained by various organizations, including IEEE and SAE International.

[0142] The term "alert" or "alert signal" refers to communication that attracts attention. Alerts may include visual, tactile, auditory alerts, and combinations of these alerts to warn the driver or occupants. These alerts enable the recipient (e.g., the driver or occupants) to react and respond quickly.

[0143] As used herein, the term "video analysis" refers to a practical solution for viewing hours of video (e.g., surveillance video) to identify events relevant to what you are looking for. Video analysis is suitable for automatically generating descriptions (so-called metadata) of what is actually happening in the video, which can be used to list occupants, seat belts, and other objects detected in the video stream (e.g., fastened seat belts, presence of occupants, postures, gestures, etc.), as well as their appearance and actions.

[0144] As used herein, the term "cybersecurity" refers to the application of technologies, processes, and controls to protect systems, networks, programs, devices, and data from cyberattacks.

[0145] As used herein, the term "cybersecurity module" refers to a module that contains applications of technologies, processes, and controls for protecting systems, networks, programs, devices, and data from cyberattacks and threats. Its purpose is to reduce the risk of cyberattacks and prevent unauthorized use of systems, networks, and technologies. It includes, but is not limited to, critical infrastructure security, application security, network security, cloud security, Internet of Things (IoT) security.

[0146] As used herein, the term "encryption" refers to the use of one or more mathematical techniques and a cipher or "key" for decrypting information to protect digital data. It refers to the conversion of information or data into code, especially to prevent unauthorized access. It may also refer to hiding information or data by converting it into code. It can also be referred to as cipher, code, encryption, encoding. A simple example is representing letters with numbers - for instance, "A" is "01", "B" is "02", and so on. For example, a message like "HELLO" would be encrypted as "0805121215", and this value would be transmitted over a network to the destination or recipient.

[0147] As used herein, the term "decryption" refers to the process of converting encrypted information back to its original format. It is typically the reverse process of encryption. It decodes the encrypted information so that only authorized users can decrypt the data, as decryption requires a key or cipher. This term can be used to describe methods of manually decrypting data or decrypting data using the correct code or key.

[0148] As used herein, the term "cybersecurity threat" refers to any potential malicious attack aimed at illegally accessing data, disrupting digital operations, or damaging information. Malicious acts include, but are not limited to, corrupting data, stealing data, or disrupting general digital life. Cybersecurity threats include, but are not limited to, malware, spyware, phishing attacks, ransomware, zero-day vulnerabilities, Trojans, advanced persistent threats, wiper attacks, data manipulation, data destruction, rogue software, malicious advertising, unpatched software, computer viruses, man-in-the-middle attacks, data breaches, denial-of-service (DoS) attacks, and other attack vectors.

[0149] As used herein, the term "hash value" can be regarded as the fingerprint of a file. The content of the file is processed through an encryption algorithm, and a unique numerical value, the hash value, is generated to identify the content of the file. If the content is modified in any way, the hash value will also change significantly. Examples of algorithms used to generate hash values: Message Digest - 5 (MD5) algorithm and Secure Hash Algorithm - 1 (SHA1).

[0150] As used herein, the term "integrity check" refers to checking the accuracy and consistency of system-related files, data, etc. This can be done using checking tools that can detect whether any critical system files have been changed, enabling system administrators to look for unauthorized system changes. For example, data integrity corresponds to the quality of data in a database and the level at which users check the quality, integrity, and reliability of the data. Data integrity checks can verify whether the data in a database is accurate and whether it operates as expected in a given application.

[0151] As used herein, the term "alert" refers to an event triggered when a component or system in a system malfunctions or does not operate as expected. When an event occurs, the system may enter an alert state. An alert indication signal is a visual signal indicating the alert state. For example, when a cybersecurity threat is detected, the system administrator can be warned by means such as a sound alert, a message, a glowing LED, a pop-up window, etc. The alert indication signal can be reported downstream of the detection device to prevent adverse situations or chain effects.

[0152] As used herein, the term "communication" refers to any coupling, connection, or interaction for exchanging information or data using electrical signals, using any system, hardware, software, protocol, or format, whether the exchange is carried out wirelessly or through a wired connection.

[0153] As used herein, the term "encryption protocol" is also referred to as a security protocol or cryptographic protocol. It is an abstract or concrete protocol that performs security-related functions and often applies cryptographic methods as a sequence of cryptographic primitives. The protocol describes how the algorithms should be used. A protocol detailed enough includes detailed information about data structures and representations, and at this time, it can be used to implement multiple interoperable versions of a program. Encryption protocols are widely used for secure application-level data transmission. Encryption protocols typically include at least some of the following aspects: key negotiation or establishment, entity authentication, symmetric encryption and message authentication material construction, secure application-level data transmission, non-repudiation methods, secret sharing methods, and secure multi-party computation. Hash algorithms can be used to verify the integrity of data. The Secure Sockets Layer (SSL) and Transport Layer Security (TLS) (the successor of SSL) are encryption protocols that network switches can use to protect data communication on the network.

[0154] As used herein, the term "network" may include the Internet, local area networks, wide area networks, or combinations thereof. A network may include one or more networks or communication systems, such as the Internet, telephone systems, satellite networks, cable television networks, and various other private and public networks. In addition, the connections may include wired connections (such as wires, cables, fiber optic lines, etc.), wireless connections, or combinations thereof. In addition, although not shown, other computers, systems, devices, and networks may also be connected to the network. A network refers to any set of devices or subsystems connected by links that connect (directly or indirectly) a set of end nodes that share resources located on or provided by network nodes. Computers communicate with each other using common communication protocols over digital interconnections. For example, a subsystem may include the cloud. The cloud refers to servers accessible via the Internet and the software and databases running on these servers.

[0155] The term "autonomous vehicle" is also known as a self-driving vehicle, driverless vehicle, robotic vehicle, and refers to a vehicle that employs vehicle automation, i.e., a ground vehicle that can sense its surrounding environment and safely operate with little or no human intervention. Autonomous vehicles incorporate a variety of sensors to sense the surrounding environment, such as thermal imaging cameras, radio detection and ranging (radar), light detection and ranging (lidar), sound navigation and ranging (sonar), global positioning system (GPS), odometers, and inertial measurement units. A control system designed for this purpose interprets the sensor information to determine an appropriate navigation path as well as obstacles and relevant signs.

[0156] As used herein, the term "semi-autonomous vehicle" refers to a vehicle that can operate for an extended period without human intervention. A semi-autonomous vehicle cannot always drive autonomously but can automate certain driving functions under ideal conditions such as highway driving. A semi-autonomous vehicle can use the "autopilot" function. In one embodiment, a semi-autonomous vehicle can stay within a lane or park itself, but cannot drive autonomously. A semi-autonomous vehicle can travel independently to some extent.

[0157] As used herein, the term "connection" refers to a communication link. It is a communication channel that connects two or more devices for data transmission. It can refer to a physical transmission medium (such as a wire) or a logical connection over a multiplexed medium (such as a wireless communication channel in telecommunications and computer networks). The channel is used for the transmission of information (such as a digital bit stream) from one or more senders to one or more receivers. The channel has a certain information transmission capacity, typically measured by its bandwidth (in hertz (Hz)) or its data rate (in bits per second). For example, vehicle-to-vehicle (V2V) communication can wirelessly exchange information about the speed, position, and direction of travel of surrounding vehicles.

[0158] As used herein, the term "connection" refers to an electrical connection established for the transmission of electricity between entities. The connection can be a daisy-chain connection. The connection can be a wired connection. The connection can be a wireless connection.

[0159] As used herein, the term "daisy-chain connection" refers to a connection of a series of interconnected entities. A daisy chain is a wiring scheme in which multiple devices are connected together in sequence or in a loop, similar to a daisy flower chain. A daisy chain can be used for the transmission of electricity between entities.

[0160] As used herein, the term "extension charger" refers to an entity that can act as an intermediate entity. An extension charger is adapted to couple multiple entities to a host vehicle. The extension charger can skip / bypass the charging of one or more entities and receive charging from a selected entity through a host intelligent charging receiver.

[0161] As used herein, the term "Level 1 charging" refers to charging using 120 - 207 volts. Each electric vehicle or plug-in hybrid vehicle can be charged at Level 1 by plugging the charging device into a common wall outlet. Level 1 charging is likely the slowest way to charge an electric vehicle. Level 1 charging typically adds 3 to 5 miles of range per hour.

[0162] As used herein, the term "Level 2 charging" refers to charging using 208 - 240 volts. Level 2 charging is the most commonly used method for daily electric vehicle charging. Level 2 charging equipment can be installed at home, at work, and in public places such as shopping malls, train stations, and other destinations. Level 2 charging can replenish 12 to 80 miles of range per hour, depending on the power output of the Level 2 charger and the maximum charging rate of the vehicle.

[0163] As used herein, the term "Level 3 charging" refers to charging using 400 - 900 volts of direct current. Level 3 charging is currently the fastest type of charging and can add 3 to 20 miles of driving range to an electric vehicle per minute. Unlike Level 1 and Level 2 charging, which use alternating current (AC), Level 3 charging uses direct current (DC).

[0164] As used herein, the term "protocol" refers to the processes required to initiate and maintain communication; a set of formal conventions that control the format and relative timing of message exchange between two communication terminals; a set of conventions that control the interaction of processes, devices, and other components within a system; a set of signaling rules used to transfer information or commands between boards connected to a bus; signal rules used to transfer information between agents; a set of semantic and syntactic rules that determine the behavior of interacting entities; a set of rules and formats (semantic and syntactic) that determine the communication behavior of simulation applications; a set of conventions or rules that control the interaction of processes or applications within a computer system or network; a set of formal conventions that control the format and relative timing of message exchange within a computer system; a set of semantic and syntactic rules that determine the behavior of functional units when achieving meaningful communication; a set of semantic and syntactic rules for exchanging information.

[0165] As used herein, the term "component" is broadly interpreted as hardware, firmware, and / or a combination of hardware, firmware, and software.

[0166] The embodiments described herein can be directed to one or more of a system, method, apparatus, and / or computer program product at any possible level of integration of technical details. The computer program product can include a computer-readable storage medium (or media) having computer-readable program instructions thereon for causing a processor to perform aspects of one or more embodiments described herein. The computer-readable storage medium can be a tangible device that can retain and store instructions for use by an instruction execution device. For example, the computer-readable storage medium can be (but is not limited to) an electronic storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a superconducting storage device, and / or any suitable combination of the foregoing devices. A non-exhaustive list of more specific examples of the computer-readable storage medium can also include the following: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a static random access memory (SRAM), a portable compact disc read-only memory (CD-ROM), a digital versatile disc (DVD), a memory stick, a floppy disk, a mechanically encoded device (such as a punch card or raised structures in grooves having instructions recorded thereon), and / or any suitable combination of the foregoing. The computer-readable storage medium as used herein does not encompass transitory signals per se, such as radio waves and / or other freely propagating electromagnetic waves, electromagnetic waves propagating through a waveguide and / or other transmission media (e.g., optical pulses through an optical fiber cable), and / or electrical signals transmitted through wires.

[0167] The computer-readable program instructions described herein can be downloaded to a corresponding computing / processing device from a computer-readable storage medium, and / or downloaded to an external computer or an external storage device via a network (e.g., the Internet, a local area network, a wide area network, and / or a wireless network). The network may include copper transmission cables, optical transmission fibers, wireless transmission, routers, firewalls, switches, gateway computers, and / or edge servers. A network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards the computer-readable program instructions for storage in a computer-readable storage medium within the respective computing / processing device. The computer-readable program instructions for performing the operations of one or more embodiments described herein may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-related instructions, microcode, firmware instructions, state-setting data, configuration data for integrated circuits, and / or source code and / or object code written in any combination of one or more programming languages, including object-oriented programming languages such as Smalltalk, C++, etc., and / or procedural programming languages such as the "C" programming language and / or similar programming languages. The computer-readable program instructions may be executed entirely on the computer, partially on the computer, executed as a stand-alone software package, partially on the computer and / or partially on a remote computer, or entirely on a remote computer and / or server. In the latter case, the remote computer may be connected to the computer via any type of network connection, including a local area network (LAN) and / or a wide area network (WAN), and / or may be connected to an external computer (e.g., via the Internet using an Internet service provider). In one or more embodiments, an electronic circuit (including, for example, a programmable logic circuit, a field-programmable gate array (FPGA), and / or a programmable logic array (PLA)) can personalize the electronic circuit by utilizing the state information of the computer-readable program instructions so as to execute the computer-readable program instructions to perform aspects of one or more embodiments described herein.

[0168] Aspects of one or more embodiments described herein are described with reference to flowcharts and / or block diagrams of methods, apparatus (systems), and computer program products according to one or more embodiments described herein. Each block in the flowchart and / or block diagrams, and combinations of blocks in the flowchart and / or block diagrams, can be implemented by computer-readable program instructions. These computer-readable program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, and / or other programmable data processing apparatus to produce a machine, such that the instructions executed by the processor of the computer or other programmable data processing apparatus create means for implementing the functions / acts specified in the flowchart and / or block diagram block. These computer-readable program instructions can also be stored in a computer-readable storage medium that can direct a computer, programmable data processing apparatus, and / or other devices to function in a particular manner, such that the computer-readable storage medium storing the instructions can constitute a manufacture including instructions that implement aspects of the functions / acts specified in the flowchart and / or block diagram block. The computer-readable program instructions can also be loaded onto a computer, other programmable data processing apparatus, and / or other devices to cause a series of operational acts to be performed on the computer, other programmable apparatus, and / or other devices to produce a computer-implemented process, such that the instructions executed on the computer, other programmable apparatus, and / or other devices implement the functions / acts specified in the flowchart and / or block diagram block.

[0169] The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and / or operation of possible implementations of systems, computer-implementable methods, and / or computer program products according to one or more embodiments described herein. In this regard, each block in the flowchart or block diagrams may represent a module, segment, and / or portion of instructions, which includes one or more executable instructions for implementing the specified logical function. In one or more alternative implementations, the functions noted in the blocks may occur out of the order noted in the figures. For example, two blocks shown in succession may be executed substantially concurrently, and / or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It should also be noted that each block of the block diagrams and / or flowchart, and combinations of blocks in the block diagrams and / or flowchart, can be implemented by special-purpose hardware systems that can perform the specified functions and / or acts and / or execute a combination of special-purpose hardware and / or computer instructions.

[0170] While the subject matter described herein is in the general context of computer-executable instructions of a computer and / or computer program product running on a computer, those skilled in the art will recognize that one or more of the embodiments described herein may also be implemented in conjunction with one or more other program modules. Program modules include routines, programs, components, data structures, etc. that perform particular tasks and / or implement particular abstract data types. Additionally, other computer system configurations, including single-processor and / or multi-processor computer systems, small computing devices, mainframe computers, and computers, handheld computing devices (e.g., PDAs, telephones), microprocessor-based or programmable consumer and / or industrial electronic devices, etc., may practice the computer-implemented methods described herein. Distributed computing environments, where remote processing devices connected by a communication network perform tasks, may also practice the aspects shown. However, an independent computer may practice one or more (if not all) of the aspects of one or more of the embodiments described herein. In a distributed computing environment, program modules may be located in local and remote memory storage devices.

[0171] As used in this application, terms such as "component", "system", "platform", "interface", etc. can refer to and / or include computer-related entities or entities related to an operating machine with one or more specific functions. The entities described herein can be hardware, a combination of hardware and software, software, or software in execution. For example, a component can be, but is not limited to, a process running on a processor, a processor, an object, an executable file, an execution thread, a program, and / or a computer. For instance, an application running on a server and the server can both be components. One or more components can reside within a process and / or an execution thread, and a component can be located on one computer and / or distributed between two or more computers. In another example, individual components can execute from various computer-readable media having various data structures stored thereon. Components can communicate via local and / or remote procedures, such as in accordance with a signal having one or more data packets (e.g., data from one component interacts with another component in a local system, a distributed system, and / or via a network such as the Internet with other systems through a signal). As another example, a component can be a device having a specific function provided by a mechanical component operated by an electrical or electronic circuit, where the electrical or electronic circuit is operated by a software and / or firmware application executed by a processor. In such a case, the processor can be internal and / or external to the device and can execute at least a portion of the software and / or firmware application. As another example, a component can be a device having a specific function provided by an electronic component without mechanical components, where the electronic component can include a processor and / or other devices to execute software and / or firmware, and the software and / or firmware at least partially imparts the functions of the electronic component. In one aspect, a component can simulate an electronic component via a virtual machine (e.g., within a cloud computing system).

[0172] In this specification, the term "processor" can refer to any computing processing unit and / or device, including but not limited to a single-core processor; a single processor with software multithreading execution capabilities; a multi-core processor; a multi-core processor with software multithreading execution capabilities; a multi-core processor with hardware multithreading technology; a parallel platform; and / or a parallel platform with distributed shared memory. Additionally, a processor can refer to an integrated circuit, an application-specific integrated circuit (ASIC), a digital signal processor (DSP), a field-programmable gate array (FPGA), a programmable logic controller (PLC), a complex programmable logic device (CPLD), discrete gate or transistor logic, discrete hardware components, and / or any combination designed to perform the functions described herein. Further, a processor can utilize nanoscale architectures, such as but not limited to molecule-based transistors, switches, and / or gates, to optimize space usage and / or enhance the performance of related devices. A combination of computing processing units can implement a processor.

[0173] In this document, terms such as "store", "storage", "data storage", "database", and any other information storage components related to the operation and function of components refer to "memory components", entities embodied in "memory", or components that include memory. The memory and / or memory components described in this document can be volatile memory or non-volatile memory, or can include volatile memory and non-volatile memory. By way of example, and not limitation, non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable ROM (EEPROM), flash memory, and / or non-volatile random access memory (RAM) (e.g., ferroelectric RAM (FeRAM)). Volatile memory can include RAM, which can be used, for example, as an external cache memory. By way of example, and not limitation, RAM can be provided in various forms, such as synchronous RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), direct Rambus RAM (DRRAM), direct Rambus dynamic RAM (DRDRAM), and / or Rambus dynamic RAM (RDRAM). In addition, the memory components of the systems and / or computer-implemented methods described in this document include, but are not limited to, these and / or any other suitable types of memory.

[0174] The embodiments described herein include only examples of systems and computer-implemented methods. Of course, in order to describe one or more embodiments, it is not possible to describe all conceivable combinations of components and / or computer-implemented methods, but one of ordinary skill in the art will recognize that many further combinations and / or permutations of one or more embodiments are possible. In addition, to the extent that the terms "comprising", "having", "owning", etc. are used in the detailed description, claims, appendices, and / or drawings, these terms are intended to be inclusive in a manner similar to the term "including", as "including" is interpreted as including when used as a transitional word in a claim.

[0175] The description of one or more embodiments is for illustrative purposes only and is not exhaustive or limiting to the embodiments described herein. Many modifications and variations will be apparent to one of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The terms used herein are best understood to explain the principles of the embodiments, the practical application, and / or the technical improvements over the technologies found in the market, and / or to enable other ordinary skilled artisans in the art to understand the embodiments described herein.

[0176] Technical Problem 1: Suppose a vehicle is stranded for a long time due to weather or traffic reasons. The problem is that when one or more vehicles lose power or fall below a safe level, there is no way to combine resources to provide power to a vehicle. Therefore, it would be great to be able to receive electricity from multiple resources (e.g., other vehicles in a similar situation) until the situation changes. For example, if a vehicle loses power, the operator can request assistance from other nearby vehicles. However, when all vehicles are below the discharge threshold (e.g., a preset charge level to ensure that the remaining charge is sufficient for the required operations without leaving the vehicle stranded), it may be impossible or insufficient to receive a charge from one vehicle. Additionally, if the vehicle is stranded, it may be difficult for a vehicle with discharge capacity to reach the vehicle in need. Therefore, a system that can receive a charge from multiple resources and through a resource chain should be provided.

[0177] Technical Solution 1: In one aspect, a system that can receive a charge from multiple resources is provided. For example, emergency adapters are provided to receive multiple inputs. The adapters can be increased or extended by adding additional adapters (e.g., assume each vehicle is equipped with an adapter having two inputs, and by adding an additional adapter from another vehicle, the vehicle can be connected to three resources at a time, i.e., one adapter + additional adapter = two adapters, and adding another adapter can make it three or more adapters). The adapters can be more than two, but the preferred adapter will have one output and two inputs. This will allow the vehicle to be connected to a charger and another power source when using the adapter. The intelligent charging system provided in the vehicle can manage and control the receipt of the charge. In one aspect, the first resource (e.g., a charging station) can be used for fast charging, while the second resource (e.g., another vehicle) can be used for slow charging. The intelligent system can select battery cells according to the type of charge. The system can monitor all health issues while receiving a charge from two or more resources. The system can switch between resources based on price (e.g., the cost associated with charging, where a charging station may be cheaper than charging from a vehicle) or type of charge (e.g., fast or slow).

[0178] Using the adapter, the system can also allow a vehicle (e.g., the vehicle) to bypass or add the charge received from another vehicle. For example, if the vehicle in need of a charge is too far away and another vehicle is closer to it, then using the adapter, the stranded vehicle can receive a charge from a distant vehicle plugged into the closer vehicle, where the closer vehicle acts as an extension cord or adds a charge in addition to the charge received from the distant vehicle. In one aspect, a daisy chain can be established where each member of the daisy chain can contribute.

[0179] As an example, Figure 1Disclosed is a system according to one or more embodiments. The system includes one or more adapters 102; a first entity 104; a second entity 106; and a host intelligent charging receiver 108. The host intelligent charging receiver 108 includes a processor 110 that stores instructions in a non-transitory memory, and when the instructions are executed, the processor 110 performs the following operations: determining the presence of one or more adapters 102 electrically coupled to the host vehicle (at step 103); identifying at least one of the first entity and the second entity electrically coupled to the host vehicle through one or more adapters (at step 105); establishing a connection between the host vehicle, the first entity, and the second entity (at step 107); analyzing at least one of a first charge and a second charge received from the first entity and the second entity respectively (at step 109); selecting at least one of the first entity and the second entity to charge one or more first battery packs of the host vehicle based on at least one of the charging specification, charging requirement, and charging cost of the host vehicle (at step 111); and providing optimal charging for one or more first battery packs of the host vehicle (at step 113). The first entity can be one of a vehicle, a charging station, and a solar panel station. The second entity can be one of a vehicle, a charging station, and a solar panel station. In one embodiment, the first entity and the second entity are similar entities. In another embodiment, the first entity and the second entity are different entities. The host intelligent charging receiver 108 can be associated with the host vehicle. The host vehicle can be one of an autonomous vehicle, a semi-autonomous vehicle, and a non-autonomous vehicle.

[0180] The host vehicle can be adjacent to the first entity and the second entity. In one embodiment, the first entity is closer to the host vehicle than the second entity, and the first entity can be used as an extended charger.

[0181] One or more adapters 102 can be extended by electrically coupling one or more subsequent adapters to receive input power from subsequent entities. One or more adapters are operable to receive input power from the first entity and the second entity simultaneously. Then, one or more adapters provide the input power received from the first entity and the second entity to the host intelligent charging receiver. One or more adapters provide optimal charging based on commands / messages received from the host intelligent charging receiver. In one embodiment, the host intelligent charging receiver includes an artificial intelligence engine. The host intelligent charging receiver can provide commands / messages to one or more adapters based on information received from the artificial intelligence engine.

[0182] In one embodiment, the artificial intelligence engine determines at least one of a travel, environmental conditions, and traffic conditions of the host vehicle and transmits fourth sensing information to the processor. The processor is operable to determine a charging requirement of the host vehicle based on at least one of a travel, environmental conditions, and traffic conditions of the host vehicle in response to the fourth sensing information.

[0183] The host intelligent charging receiver can provide commands / messages to one or more adapters based on information received from at least one of the sensor module and the artificial intelligence engine. Then, the one or more adapters 102 provide optimal charging for the host vehicle. In an embodiment, the one or more adapters 102 include a plurality of devices. The plurality of devices includes a plurality of sockets. The plurality of sockets includes a plurality of male sockets. The plurality of sockets may include a plurality of female sockets. The plurality of sockets may further include a plurality of female sockets and a plurality of male sockets.

[0184] In one embodiment, the system further includes a sensor module. The sensor module may be associated with the host vehicle. The sensor module may also be associated with the plurality of devices. In one embodiment, the sensor module includes at least one of the following: one or more temperature sensors, one or more cameras, one or more giant magnetoresistance sensors, one or more weight sensors, one or more weighing units, one or more infrared sensors, one or more proximity sensors, one or more ultrasonic sensors, one or more light detection and ranging (LIDAR) sensors, one or more voltage sensors, one or more light sensors, one or more capacitive weighing units, one or more limit switches, one or more proximity sensors, and one or more accelerometers. In one embodiment, the sensor module is electrically coupled and communicatively coupled to the one or more adapters and the host intelligent charging receiver.

[0185] In one embodiment, the sensor module determines the presence of one or more adapters and transmits first sensing information. As an example, one or more limit switches determine the presence of one or more adapters by contacting the one or more adapters and transmitting first sensing information. The processor determines the presence of the one or more adapters based on the first sensing information received from the sensor module. As another example, one or more cameras may capture at least one of one or more images and one or more videos of the plurality of devices. The one or more cameras may transmit the sensing information to the processor. The processor includes an artificial intelligence engine. The processor using artificial intelligence may perform image analysis (or video analysis) and analyze at least one of the one or more images and one or more videos of the plurality of devices. The processor extracts meaningful content (e.g., shape, size, color, pattern, text, language, etc.) and determines the presence of one or more adapters based on a predefined data set. The artificial intelligence engine may include a machine learning algorithm (e.g., linear regression) that may be trained using the predefined data set. The machine learning algorithm may compare the meaningful content with the predefined data set and generate a matching score. Based on the matching score, the processor determines the presence of the one or more adapters.

[0186] The host vehicle is electrically coupled to at least one of a first entity 104 and a second entity 106 through one or more adapters 102. In one embodiment, a single adapter may be configured to electrically couple the first entity 104 and the second entity 106. In another embodiment, a single adapter may be expandable to have more sockets or devices to expand the coupling of multiple entities to the host vehicle by inserting one or more additional adapters.

[0187] The processor is operable to identify at least one of a first entity and a second entity electrically coupled to the host vehicle through one or more adapters based on second sensing information received from the sensor module. In one embodiment, the sensor module (e.g., one or more voltage sensors) measures a first voltage and a second voltage received from the first entity and the second entity respectively through the one or more adapters and transmits the second sensing information. Then, the processor identifies at least one of a first entity and a second entity electrically coupled to the host vehicle through the one or more adapters based on the second sensing information received from the sensor module. The processor identifies the types of the first entity and the second entity based on the second sensing information received from the sensor module. For example, when the voltage is less than a predefined threshold, the processor determines that the entity is a vehicle. For example, when the voltage is greater than a predefined threshold, the processor determines that the entity is a charging station.

[0188] Then, the processor establishes a connection between the host vehicle, the first entity 104, and the second entity 106. The processor may establish the connection to form a network. The connection may be a daisy-chain connection, where each member can contribute and / or receive charging from the network. In one embodiment, the members (i.e., the host vehicle, the first entity 104, and the second entity 106) are connected in series. A daisy-chain connection involves connecting multiple entities in series, where one charger is connected to another charger. A daisy-chain connection may also be useful in scenarios where charging a single electric vehicle from multiple entities is required. A daisy-chain connection may also be useful in scenarios where charging multiple electric vehicles is required and the available power source is limited, or when simplifying infrastructure setup at a particular location. A daisy-chain connection may also be useful in scenarios where the host vehicle has less charging, and the first entity can be used as an extension cord to receive charging from the second entity and provide optimal charging to the host vehicle. A daisy-chain connection can charge multiple electric vehicles in parallel simultaneously.

[0189] In one embodiment, the host vehicle, the first entity, and the second entity are connected in series via one or more charging cables. In one embodiment, the connection is a wireless connection. In one embodiment, the connection is a wired connection. In one embodiment, the connection is adapted to transfer power between the host vehicle, the first entity, and the second entity. The charging transfer between the host vehicle, the first entity, and the second entity can be carried out via at least one of a wired connection and a wireless connection.

[0190] The host vehicle may also be communicatively coupled to at least one of the first entity 104 and the second entity 106 via the connection. The host vehicle may be communicatively coupled via one of V2I (Vehicle-to-Infrastructure), V2I (Vehicle-to-Infrastructure), V2N (Vehicle-to-Network), V2V (Vehicle-to-Vehicle), V2P (Vehicle-to-Pedestrian), V2D (Vehicle-to-Device), and V2G (Vehicle-to-Grid) as well as vehicle-to-everything (V2X) communication. The host vehicle may be configured to communicate information or data (e.g., charging status, SoH, SoC, charging duration, charging time, charging sequence, charging requirements, charging specifications, preferred charging cost, etc.) with the first entity 104 and the second entity 106. The information may include messages or commands. In one embodiment, the first entity includes a first intelligent charging receiver, and the second entity includes a second intelligent charging receiver. The first intelligent charging receiver is configured to communicate with the host intelligent charging receiver 108 and the second intelligent charging receiver. The second intelligent charging receiver is configured to communicate with the host intelligent charging receiver 108 and the first intelligent charging receiver. In one embodiment, the first intelligent charging receiver, the host intelligent charging receiver 108, and the second intelligent charging receiver are configured to communicate with each other.

[0191] In one embodiment, the system is operable to receive at least one of a first charge and a second charge from a first entity and a second entity. In another embodiment, the system is operable to simultaneously receive the first charge and the second charge from the first entity and the second entity respectively through one or more adapters. The first charge received from the first entity includes one of level 1 charging, level 2 charging, and level 3 charging. The second charge received from the second entity includes one of level 1 charging, level 2 charging, and level 3 charging.

[0192] In another embodiment, the system is operable to combine the first charge and the second charge and provide an optimal charge based on the charging specifications of the host vehicle. In one embodiment, the system is operable to select one of the first charge and the second charge and provide an optimal charge based on at least one of the charging specifications, charging requirements, and charging costs of the host vehicle.

[0193] In one embodiment, the sensor module determines parameters related to at least one of the state of health (SoH), state of charge (SoC), host vehicle temperature, and ambient temperature and transmits third sensing information. The processor is operable to determine the charging requirements of the host vehicle based on the third sensing information received from the sensor module.

[0194] In one embodiment, the artificial intelligence engine communicates with one or more databases and extracts at least one of the itinerary, environmental conditions, traffic conditions, and charging costs of the host vehicle. The artificial intelligence engine communicates at least one of the itinerary, environmental conditions, traffic conditions, and charging costs of the host vehicle as fourth sensing information. Then, the processor is operable to determine the charging requirements of the host vehicle based on at least one of the third sensing information received from the sensor module and the fourth sensing information received from the artificial intelligence engine.

[0195] In one embodiment, the sensor module captures one of one or more images and one or more videos of at least one of the host vehicle, the first entity, and the second entity and transmits fifth sensing information. Then, the processor identifies the identity of at least one of the host vehicle, the first entity, and the second entity based on the fifth sensing information received from the sensor module. In one embodiment, the processor analyzes one or more images and one or more videos of at least one of the host vehicle, the first entity, and the second entity and identifies the identity of at least one of the host vehicle, the first entity, and the second entity by performing image analysis.

[0196] The processor is operable to automatically provide optimal charging to one or more first battery packs of the host vehicle based on at least one of a charging specification, a charging requirement, and a charging cost of the host vehicle. In one embodiment, the one or more first battery packs include a plurality of battery cells. In one embodiment, the charging duration includes a time period. In one embodiment, the one or more first battery packs include one of one or more identical batteries and one or more non-identical batteries. In one embodiment, the one or more first battery packs include one of one or more identical batteries and one or more non-identical batteries. The charging requirement includes at least one of a charging sequence, a charging time, and a charging duration. The charging sequence includes at least one of level 1 charging, level 2 charging, and level 3 charging. Level 1 charging includes trickle charging. Level 2 charging includes normal charging. Level 3 charging includes fast charging. In one embodiment, the charging sequence includes a combination of at least one of level 1 charging corresponding to a first portion of the one or more first battery packs, level 2 charging corresponding to a second portion of the one or more first battery packs, and level 3 charging corresponding to a third portion of the one or more first battery packs. In one embodiment, the charging sequence includes a combination of at least one of level 1 charging corresponding to a first charging time period, level 2 charging corresponding to a second charging time period, and level 3 charging corresponding to a third charging time period. The charging time includes a combination of at least one of a first charging time period, a second charging time period, and a third charging time period.

[0197] In another embodiment, the processor is operable to automatically provide optimal charging to one or more first battery packs of the host vehicle based on at least one of a charging specification, a charging requirement, and a charging cost of the host vehicle. In another embodiment, the processor is operable to receive user input and provide optimal charging to one or more first battery packs of the host vehicle based on the user input. The processor enables the user to provide the user input by selecting one of the drop-down menus through one of the vehicle computer system and an external device. In one embodiment, the drop-down menu includes an option of one of a charging specification, a charging requirement, and a charging cost of the host vehicle. The external device includes one of a smart phone, a tablet computer, a computer, a desktop computer, a tablet computer, a handheld device, and a smart watch.

[0198] As an example, Figure 2Disclosed is a method according to one or more embodiments. The method includes the following technical steps: determining the presence of one or more adapters electrically coupled to a host vehicle (at step 203); identifying at least one of a first entity and a second entity electrically coupled to the host vehicle via one or more adapters (at step 205); establishing a connection among the host vehicle, the first entity, and the second entity (at step 207); analyzing at least one of a first charge and a second charge received from the first entity and the second entity respectively (at step 209); selecting at least one of the first entity and the second entity for charging one or more first battery packs of the host vehicle based on at least one of the charging specification, charging requirement, and charging cost of the host vehicle (at step 211); and providing optimal charging to one or more first battery packs of the host vehicle (at step 213).

[0199] The method further includes: determining at least one of the itinerary, environmental conditions, and traffic conditions of the host vehicle through an artificial intelligence engine and communicating fourth sensing information. The method further includes: determining the charging requirement of the host vehicle based on at least one of the itinerary, environmental conditions, and traffic conditions of the host vehicle.

[0200] The method further includes: determining the presence of one or more adapters based on the first sensing information received from a sensor module. The method further includes: simultaneously receiving the first charge and the second charge from the first entity and the second entity respectively through one or more adapters. The method further includes: combining the first charge and the second charge and providing optimal charging based on the charging specification of the host vehicle. The method further includes: selecting one of the first charge and the second charge and providing optimal charging based on at least one of the charging specification and charging cost of the host vehicle.

[0201] In one embodiment, the method further includes: transmitting third sensing information through a sensor module based on the determination of parameters related to the state of health (SoH), state of charge (SoC), host vehicle temperature, environmental temperature, and / or charging status. In one embodiment, the method further includes: determining the charging requirement of the host vehicle based on the third sensing information received from the sensor module.

[0202] In one embodiment, the method further includes: determining the charging requirement of the host vehicle based on at least one of the third sensing information received from the sensor module and the fourth sensing information received from the artificial intelligence engine. In one embodiment, the method further includes: communicating with one or more databases and using the artificial intelligence engine to extract at least one of the itinerary, environmental conditions, and traffic conditions of the host vehicle and the charging cost, and sharing them as the fourth sensing information.

[0203] In one embodiment, the method further includes: identifying the identity of at least one of the host vehicle, the first entity, and the second entity. The method further includes: capturing, by a sensor module, one or more images and one of one or more videos of at least one of the host vehicle, the first entity, and the second entity, and communicating fifth sensing information. The method further includes: analyzing one or more images and one of one or more videos of at least one of the host vehicle, the first entity, and the second entity, and identifying the identity of at least one of the host vehicle, the first entity, and the second entity by performing image analysis.

[0204] In one embodiment, the method further includes: automatically providing optimal charging to one or more first battery packs of the host vehicle based on at least one of the charging specifications, charging requirements, and charging costs of the host vehicle. In another embodiment, the method further includes: receiving user input and providing optimal charging to one or more first battery packs of the host vehicle based on the user input.

[0205] As an example, Figure 3 Disclosed is a non-transitory computer-readable storage medium according to one or more embodiments. The non-transitory computer-readable storage medium includes a series of instructions that, when executed by a processor, cause: determining the presence of one or more adapters electrically coupled to the host vehicle (at step 303); identifying at least one of the first entity and the second entity electrically coupled to the host vehicle through one or more adapters (at step 305); establishing a connection between the host vehicle, the first entity, and the second entity (at step 307); analyzing at least one of the first charging and the second charging received from the first entity and the second entity respectively (at step 309); selecting at least one of the first entity and the second entity to charge one or more first battery packs of the host vehicle based on at least one of the charging specifications, charging requirements, and charging costs of the host vehicle (at step 311); and providing optimal charging to one or more first battery packs of the host vehicle (at step 313).

[0206] In one embodiment, the non-transitory computer-readable medium further causes: communicating fourth sensing information through an artificial intelligence engine based on a determination of at least one of the itinerary, environmental conditions, and traffic conditions of the host vehicle. The non-transitory computer-readable medium further causes: determining the charging requirements of the host vehicle based on at least one of the itinerary, environmental conditions, and traffic conditions of the host vehicle.

[0207] In one embodiment, the non-transitory computer-readable medium further causes: determining the presence of one or more adapters based on sensing information received from a sensor module. The non-transitory computer-readable medium further causes: simultaneously receiving a first charge and a second charge from a first entity and a second entity, respectively, via the one or more adapters. In one embodiment, the non-transitory computer-readable medium further causes: combining the first charge and the second charge and providing an optimal charge based on the charging specifications of the host vehicle. In one embodiment, the non-transitory computer-readable medium further causes: selecting one of the first charge and the second charge and providing an optimal charge based on at least one of the charging specifications of the host vehicle and the charging cost.

[0208] In one embodiment, the non-transitory computer-readable medium further causes: determining, via a sensor module, parameters related to at least one of a state of health (SoH), a state of charge (SoC), a host vehicle temperature, and an ambient temperature, and communicating third sensing information. The non-transitory computer-readable medium further causes: determining the charging requirements of the host vehicle based on the third sensing information received from the sensor module. In one embodiment, the non-transitory computer-readable medium further causes: communicating with one or more databases and extracting at least one of a trip, ambient conditions, and traffic conditions of the host vehicle, and a charging cost. In one embodiment, the non-transitory computer-readable medium further causes: determining the charging requirements of the host vehicle based on at least one of the third sensing information received from the sensor module and fourth sensing information received from an artificial intelligence engine (e.g., at least one of a trip, ambient conditions, and traffic conditions of the host vehicle).

[0209] In one embodiment, the non-transitory computer-readable medium further causes: capturing, via a sensor module, one of one or more images and one or more videos of at least one of the host vehicle, the first entity, and the second entity, and communicating fifth sensing information. The non-transitory computer-readable medium further causes: identifying the identity of at least one of the host vehicle, the first entity, and the second entity based on the fifth sensing information received from the sensor module. In one embodiment, the non-transitory computer-readable medium further causes: analyzing one or more images and one or more videos of at least one of the host vehicle, the first entity, and the second entity, and identifying the identity of at least one of the host vehicle, the first entity, and the second entity by performing image analysis.

[0210] In one embodiment, the non-transitory computer-readable medium further causes: automatically providing an optimal charge to one or more first battery packs of the host vehicle based on at least one of the charging specifications, charging requirements, and charging cost of the host vehicle. In another embodiment, the non-transitory computer-readable medium further causes: receiving user input and providing an optimal charge to one or more first battery packs of the host vehicle based on the user input.

[0211] By way of example,Figure 4 A block diagram showing a system according to one or more embodiments. The system includes a host vehicle adjacent to a first entity and a second entity. The host vehicle includes a host intelligent charging receiver capable of receiving charging from a plurality of entities (e.g., the first entity, the second entity, etc.). The first entity may be closer to the host vehicle than the second entity.

[0212] The host intelligent charging receiver includes a processor. The processor is configured to determine the presence of an adapter and identify the first entity and the second entity. The processor is also capable of determining the type of the entity (e.g., charging station, vehicle, etc.). The processor is also capable of determining the type of charging received from the first entity and the second entity. The type of charging may be fast charging, slow charging, regular charging, etc.

[0213] The processor includes an artificial intelligence engine that determines at least one of the travel itinerary, environmental conditions, and traffic conditions of the host vehicle. Then, the artificial intelligence engine automatically determines the charging requirements of the host vehicle. The artificial intelligence engine may determine the charging requirements based on at least one of the travel itinerary, environmental conditions, and traffic conditions of the host vehicle. For example, if the travel itinerary (e.g., travel plan) of the host vehicle is about 100 kilometers, the charging requirements of the host vehicle are relatively high, so the host intelligent charging receiver may request and receive charging from a plurality of entities based on the state of charge (SoC) of the plurality of entities. For another example, if the travel itinerary (e.g., travel plan) of the host vehicle is about 10 kilometers, the charging requirements of the host vehicle are relatively low, so the host intelligent charging receiver may request and receive charging from a single entity based on the state of charge (SoC) of the single entity. Similarly, the artificial intelligence engine may determine the charging requirements based on traffic conditions. For example, if the host vehicle is stuck in traffic congestion, the charging requirements of the host vehicle are very high, so the host intelligent charging receiver may request and receive predefined charging according to the state of charge (SoC) of a plurality of entities or a single entity. Similarly, the artificial intelligence engine may determine the charging requirements according to traffic conditions. For example, if the host vehicle is stuck in traffic congestion, the charging requirements of the host vehicle are very high, so the host intelligent charging receiver may request and receive predefined charging according to the state of charge of a plurality of entities.

[0214] The first entity may include a first intelligent charging receiver, and the second entity may include a second intelligent charging receiver. The host intelligent charging receiver is operable to transmit a message and / or command to at least one of the first intelligent charging receiver and the second intelligent charging receiver and request charging for one or more first battery packs of the host vehicle. The authorized personnel of the first entity and the second entity may approve or reject the request. The first intelligent charging receiver and the second intelligent charging receiver may transmit power based on the command and / or message to provide charging to the host vehicle.

[0215] For example, Figure 5Disclosed is a battery pack 502 of a host vehicle including a single battery according to one or more embodiments. The battery pack 502 herein includes a single battery. The battery includes a plurality of battery cells 504. The battery pack includes a first portion X, a second portion Y, and a third portion Z. The first portion X may include a first plurality of the plurality of battery cells of the battery. The second portion Y may include a second plurality of the plurality of battery cells of the battery. The third portion Z may include a third plurality of the plurality of battery cells of the battery.

[0216] The first portion X, the second portion Y, and the third portion Z may be classified based on the health state information of their respective portions. The first portion X may include health state information. The second portion Y may include second health state information. The third portion Z may include third health state information. In an embodiment, the first portion may refer to the portion of the battery having degraded battery cells. The second portion may refer to the portion of the battery having healthy battery cells. The third portion may refer to the portion of the battery having moderately degraded battery cells.

[0217] For example, Figure 6 Disclosed is a battery pack of a host vehicle including a plurality of batteries according to one or more embodiments. The battery pack herein includes a first battery 602a, a second battery 602b, and a third battery 602c. The first battery 602a, the second battery 602b, and the third battery 602c may be the same battery. The first battery 602a, the second battery 602b, and the third battery 602c may be different batteries. In one embodiment, each battery of the battery pack may include an equal capacity to store and deliver electrical power. In another embodiment, each battery of the battery pack may include a different capacity to store and deliver electrical power.

[0218] The first battery 602a may include a plurality of first battery cells 604a, the second battery 602b may include a plurality of second battery cells 604b, the third battery 602c may include a plurality of third battery cells 604c, each battery of the battery pack is electrically connected, and the host intelligent charging receiver receives electrical energy and charges each battery of the electrically connected battery pack. The host intelligent charging receiver may receive electrical energy randomly, in series, or in parallel and charge each battery of the battery pack.

[0219] The host intelligent charging receiver can charge at least one of the first part X, the second part Y, and the third part Z of the battery pack. The first part X of the battery pack refers to the degraded battery cells in each battery of the battery pack (X = X1 + X2 + X3). The second part Y of the battery pack refers to the healthy battery cells in each battery of the battery pack (Y = Y1 + Y2 + Y3). The third part Z of the battery pack refers to the moderately degraded battery cells in each battery of the battery pack (Z = Z1 + Z2 + Z3). The healthy battery cells can be located continuously or discontinuously within the same battery. Similarly, the degraded and moderately degraded batteries can be located continuously or discontinuously within the same battery.

[0220] The host intelligent charging receiver is configured to map the battery pack based on the health status information. In one embodiment, the host intelligent charging receiver maps at least one of the degraded battery cells, the healthy battery cells, and the moderately degraded battery cells of the battery pack. After performing the mapping of the battery pack, the host intelligent charging receiver determines the charging sequence based on the health status information and the available charging time. The host intelligent charging receiver can assign the charging sequence to a specific part of the battery pack. In one embodiment, the host intelligent charging receiver assigns the charging sequence only to the healthy battery cells and the moderately degraded battery cells of the battery pack. The host intelligent charging receiver can ignore charging the degraded battery cells.

[0221] As an example, Figure 7 According to one or more embodiments, a battery pack including a battery 702 and a battery management system 706 is schematically shown. The battery 702 further includes a plurality of battery cells 704. The battery management system 706 can include a microprocessor, a microcontroller, a programmable digital signal processor, or another programmable device. The battery management system 706 can also or alternatively include an application-specific integrated circuit, a programmable gate array, or a programmable array logic, a programmable logic device, or a digital signal processor. When the battery management system 706 includes a programmable device (such as the above microprocessor, microcontroller, or programmable digital signal processor), the processor can further include computer-executable code for controlling the operation of the programmable device. In one embodiment, the battery management system 706 is located within a vehicle. The battery management system 706 determines the health status of the battery pack and communicates it to the host intelligent charging receiver.

[0222] In one embodiment, the battery management system 706 is configured to: measure the first battery property and temperature of the battery in the vehicle; (i) calculate the health status of the battery cells of the determined battery property using a predetermined model (ii) provide a function f to estimate the battery cell degradation rate; update the estimated health status in the previous time step according to the following:

[0223] SoH est ←SoH est+f·dt+K·(SoH calc -SoH est )

[0224] where K is a gain factor depending on the vehicle operating conditions, and K is modified for each time step using a reinforcement learning agent.

[0225] In another embodiment, the battery management system 706 estimates the state of health characteristics of the battery pack in the vehicle. The estimation of SOH includes: charging and discharging the battery pack at least once within the upper region of the state of charge (SOC) window. In this case, within the first time period, the battery pack is charged to a first predetermined level within the upper region of the SOC window. Then, within the second time period, a first charging current pulse discharges the battery pack to push the SOC level of the battery pack to a level above the first predetermined level and outside the SOC window. Then, the motor discharges the battery pack to a second predetermined level within the SOC window.

[0226] The estimation of SOH further includes: charging and discharging the battery pack at least once within the lower region of the SOC window. In this case, within the third time period, the battery pack is charged to a third predetermined level within the SOC window. Then, the motor discharges the battery pack to a fourth predetermined level within the SOC window. Then, within the fourth time period, a second current pulse discharges the battery pack to push the SOC level of the battery pack to a level below the fourth predetermined level and below the SOC window.

[0227] The estimation of SOH further includes: using the achieved levels outside the SOC window, calibrating through the battery management system 706 in the vehicle to determine the correct upper and lower edges of the current SOC window; and estimating the SOH characteristics of the battery pack during charging and discharging using the battery management system 706, and determining the condition of the battery pack compared with a new unused battery pack by comparing the current SOC window with a standard SOC window. In one embodiment, the first and third time periods are longer than the second and fourth time periods respectively. In another embodiment, the first predetermined level represents a higher voltage than the second predetermined level, and the third predetermined level represents a higher voltage than the fourth predetermined level.

[0228] As an example, Figure 8 shows a message sent by a host intelligent charging receiver to a first entity according to one or more embodiments. In the embodiment, the message is similar to the HL7 protocol. Figure 8 The example message shown includes fields such as vehicle ID, charging time, charging duration, charging sequence, state of charge (SoC), pairing ID, state of health, extended charging, etc. The first entity herein may be a vehicle.

[0229] The vehicle ID can be a serial identification number or a tag associated with the electric vehicle, which is configured to identify and locate the electric vehicle. The charging time can be a predetermined time / assigned time provided for optimal charging of the vehicle. The state of health refers to the state of health information of different parts of the battery pack. The state of charge refers to the state of charge information of different parts of the battery pack. Extended charging means that in addition to the charging received from the second entity, charging is also provided by the first entity. The extended charging field can have an attribute of "yes" or "no". If it is "yes", the host vehicle can receive charging from the first entity in addition to the charging received from the second entity. If it is "no", the host vehicle can only receive charging from the first entity or the second entity. After receiving the message, the first entity decodes and extracts the information for charging the vehicle. Then, the first intelligent charging receiver in the first entity can supply power according to the information received through the message to optimally charge the host vehicle.

[0230] As an example, Figure 9 Shows a message sent by a host intelligent charging receiver to a first entity according to one or more embodiments. In one embodiment, the message is similar to the HL7 protocol. Figure 9 The example message shown in includes fields such as vehicle ID, charging time, charging duration, charging sequence, state of charge (SoC), pairing ID, and state of health. The first entity here can be a charging station.

[0231] The vehicle ID can be a serial identification number, or a tag associated with the electric vehicle, which is configured to identify and locate the electric vehicle. The charging time can be a predetermined time / assigned time provided for optimal charging of the vehicle. The state of health refers to the state of health information of different parts of the battery pack. The state of charge refers to the state of charge information of different parts of the battery pack. Extended charging means that in addition to the charging received from the second entity, charging is also provided by the first entity. The extended charging field can have an attribute of "yes" or "no". If it is "yes", the host vehicle can receive charging from the first entity in addition to the charging received from the second entity. If it is "no", the host vehicle can receive charging only from the first entity or the second entity. After receiving the message, the first entity decodes and extracts the information for charging the vehicle. Then, the first intelligent charging receiver in the first entity can supply power according to the information received through the message to optimally charge the host vehicle.

[0232] As an example, Figure 10 Shows a view of an embodiment where the main adapter has more sockets relative to the power extension cord. The main adapter can be an adapter electrically coupled to the host vehicle. The main adapter can include multiple sockets. The multiple sockets can be at least one of multiple female sockets and multiple male sockets.

[0233] In one embodiment, the main adapter includes two input sockets and an output cable. By coupling one or more subsequent / additional adapters to the main adapter, the main adapter can be expanded to have more sockets (i.e., more inputs). The subsequent adapter coupled to the main adapter provides means for receiving more inputs. The main adapter expanded by coupling an additional adapter includes means similar to Figure 10 the power extension cord shown. The power extension cord can provide multiple outputs from a single input, while the main adapter provides a single output from multiple inputs.

[0234] As an example, Figure 11 shows power transfer between a host vehicle, a first entity, and a second entity according to one or more embodiments. The first entity and the second entity described herein can be a first vehicle and a second vehicle, respectively. The first entity can be an intermediate entity that receives charging from the second entity and provides the charging to the battery pack of the host vehicle.

[0235] The first entity can receive a command / message from the host intelligent charging receiver of the host vehicle to provide charging to the host vehicle. The first entity can act as an extended charger, which is configured to provide only a second charge to the host vehicle and bypass the first charge. The second charge can be the charge received from the second entity. The first charge can be the charge received from the first entity. In an embodiment, the first entity can provide the first charge and the second charge to the host vehicle.

[0236] In one embodiment, the host intelligent charging receiver can receive the first charge and the second charge. In another embodiment, the host intelligent charging receiver can receive the first charge without receiving the second charge. In one embodiment, the host vehicle, the first entity, and the second entity are connected by a daisy chain connection. The members of the daisy chain connection form a network. Each member of the daisy chain connection can contribute and / or utilize charging.

[0237] As an example, Figure 12 shows power transfer between a host vehicle, a first entity, and a second entity according to one or more embodiments. The first entity and the second entity described herein can be a first charging station and a second charging station, respectively.

[0238] The first entity and the second entity can receive a command / message from the host intelligent charging receiver of the host vehicle to provide charging to the host vehicle. The first entity can act as an extended charger, which is configured to provide only a second charge to the host vehicle and bypass the first charge. The second charge can be the charge received from the second entity. The first charge can be the charge received from the first entity. In an embodiment, the first entity can provide the first charge and the second charge to the host vehicle.

[0239] In one embodiment, the host vehicle, the first entity, and the second entity are connected via a daisy chain connection. The members of the daisy chain connection form a network. Each member of the daisy chain connection can contribute and / or utilize charging.

[0240] As an example, Figure 13 Shows power transfer between a host vehicle, a first entity, and a second entity according to one or more embodiments. In this embodiment, the second entity can be a charging station, and the first entity can be a vehicle. The host vehicle including the host intelligent charging receiver is capable of receiving charging from the first entity (e.g., a vehicle) and the second entity (e.g., a charging station).

[0241] Technical problem 2: Suppose the vehicle is stranded for a long time due to weather or traffic. The problem is that when one or more vehicles lose power or the power drops below a safe level, there is no way to combine resources to power a single vehicle. Therefore, it would be great to be able to receive power from multiple resources (e.g., other vehicles in a similar situation) until the situation changes. For example, if a vehicle loses power, the operator can request help from other nearby vehicles. However, when all vehicles are below the discharge threshold (e.g., a preset charge level to ensure that the remaining charge is sufficient for the required operations without leaving the vehicle stranded), it may be impossible or insufficient to receive charging from one vehicle. Additionally, if the vehicle is stranded, it may be difficult for a vehicle with discharging ability to reach the vehicle in need. Therefore, a system that can receive charging from multiple resources and through a resource chain should be provided.

[0242] Technical solution 2: Provide an adapter to receive multiple inputs. It should be noted that the number of adapters can be increased by adding additional adapters (e.g., assuming each vehicle is equipped with an adapter with two inputs and adding an additional adapter from another vehicle, the vehicle can be connected to three resources simultaneously, one adapter + adapter = two adapters, and adding another adapter can make it three or more). The adapter can have more than two inputs, but the preferred adapter will include an output with two inputs. This will allow the vehicle to connect to a charger and another power source when using the adapter. The intelligent charging system provided in the vehicle can manage and control the receipt of charging.

[0243] In one aspect, the second entity / resource (e.g., a charging station) can be used for fast charging, while the first entity / resource (e.g., another vehicle) can be used for slow charging. The intelligent system can select battery cells according to the charging type. The system can monitor all health issues while receiving charging from two or more resources. The system can switch between resources based on price (e.g., the cost associated with charging, where the charging station may be cheaper than charging from a car) or charging type (e.g., fast or slow).

[0244] Using an adapter, the system can also allow a vehicle to bypass or add charging received from another vehicle. For example, if the vehicle in need of charging is too far away and another vehicle is closer to it, then using an adapter, the stranded vehicle can receive charging from a distant vehicle plugged into the closer vehicle, where the closer vehicle acts as an extension cord, or add charging in addition to the charging received from the distant vehicle. In one aspect, a daisy chain can be established where each member of the daisy chain can contribute.

[0245] As an example, Figure 14 FIG. shows a system according to one or more embodiments. The system includes one or more adapters 1402; a first entity 1404; a second entity 1406; and a host intelligent charging receiver 1408. The host intelligent charging receiver 1408 includes a processor 1410 that stores instructions in a non-transitory memory, and when the instructions are executed, the processor 1410 performs the following operations: determining the presence of one or more adapters 1402 electrically coupled to the host vehicle (at step 1403); identifying at least one of the first entity 1404 and the second entity 1406 electrically coupled to the host vehicle through the one or more adapters 1402 (at step 1405); establishing a connection between the host vehicle, the first entity 1404, and the second entity 1406 (at step 1407); transmitting a command to one of the first entity 1404 and the second entity 1406 to act as an extension charger based on a first charge and a second charge received from the first entity 1404 and the second entity 1406 respectively (at step 1409); and providing optimal charging for one or more battery packs of the host vehicle by providing at least one of the first charge and the second charge (at step 1411). The first entity 1404 can be one of a vehicle, a charging station, and a solar panel station. The second entity 1406 can be one of a vehicle, a charging station, and a solar panel station. In one embodiment, the first entity 1404 and the second entity 1406 are similar entities. In another embodiment, the first entity 1404 and the second entity 1406 are different entities. In one embodiment, one or more battery packs include a plurality of battery cells.

[0246] The vehicle is adjacent to a first entity 1404 and a second entity 1406. The first entity 1404 is closer to the host vehicle than the second entity 1406. A processor 1410 is operable to identify at least one of the first entity 1404 and the second entity 1406 that is electrically coupled to the host vehicle via one or more adapters 1402. In one embodiment, the processor 1410 includes an artificial intelligence engine. The artificial intelligence engine analyzes the charging received from the first entity 1404 and the second entity 1406. Then, the artificial intelligence engine conveys the information to the host intelligent charging receiver 1408. Then, the processor 1410 identifies at least one of the first entity 1404 and the second entity 1406 based on the information. The processor 1410 is also capable of identifying the types of the first entity 1404 and the second entity 1406 based on the information.

[0247] In one embodiment, one or more adapters 1402 are expanded to have more outlets by electrically coupling one or more subsequent adapters to receive input power from subsequent entities. One or more adapters 1402 are operable to receive input power simultaneously from the first entity 1404, the second entity 1406, and other subsequent entities coupled via subsequent entities. One or more adapters 1402 provide the input power received from the first entity 1404 and the second entity 1406 to the host intelligent charging receiver.

[0248] In one embodiment, the system further includes a sensor module. The sensor module includes at least one of one or more temperature sensors, one or more cameras, one or more giant magnetoresistive sensors, one or more weight sensors, one or more weighing units, one or more infrared sensors, one or more proximity sensors, one or more ultrasonic sensors, one or more light detection and ranging (LIDAR) sensors, one or more voltage sensors, one or more light sensors, one or more capacitive weighing units, one or more limit switches, one or more proximity sensors, and one or more accelerometers. In one embodiment, the sensor module is electrically coupled and communicatively coupled to one or more adapters and the host intelligent charging receiver 1408.

[0249] In one embodiment, the processor 1410 identifies at least one of the first entity and the second entity based on at least one of one or more images and one or more videos captured by the sensor module. The processor 1410 analyzes at least one of one or more images and one or more videos captured by the sensor module and extracts information via the artificial intelligence engine to identify at least one of the first entity 1404 and the second entity 1406.

[0250] In another embodiment, the sensor module captures one or more images and one or more videos of at least one of the host vehicle, the first entity 1404, and the second entity 1406 and transmits fifth sensing information. The processor 1410 identifies the identity of at least one of the host vehicle, the first entity 1404, and the second entity 1406 based on the fifth sensing information received from the sensor module. In one embodiment, the processor analyzes one or more images and one or more videos of at least one of the host vehicle, the first entity 1404, and the second entity 1406 and identifies the identity of at least one of the host vehicle, the first entity 1404, and the second entity 1406 by performing image analysis.

[0251] The host vehicle, the first entity 1404, and the second entity 1406 are interconnected to form a network. The processor 1410 establishes a connection between the host vehicle, the first entity 1404, and the second entity 1406. In one embodiment, the connection between the host vehicle, the first entity 1404, and the second entity 1406 is a daisy-chain connection. In one embodiment, the host vehicle, the first entity 1404, and the second entity 1406 are connected in series via one or more charging cables. In one embodiment, the connection is a wireless connection. In another embodiment, the connection is a wired connection. The connection may be adapted to transfer power between the host vehicle, the first entity 1404, and the second entity 1406.

[0252] The processor 1410 enables the host intelligent charging receiver to communicate (i.e., transmit and receive) information from the first entity 1404 and the second entity 1406. In an embodiment, the host vehicle may communicate a message / command to one of the first entity 1404 and the second entity 1406. The host vehicle may be communicatively and electrically coupled to at least one of the first entity 1404 and the second entity 1406.

[0253] The first entity 1404 may include a first intelligent charging receiver. The second entity 1406 may include a second intelligent charging receiver. In one embodiment, the host intelligent charging receiver is communicatively coupled to the second intelligent charging receiver of the first entity and the third intelligent charging receiver of the second entity. The host intelligent charging receiver, the second intelligent charging receiver, and the third intelligent charging receiver may be operable to perform one of contributing power transfer and available power transfer with each other.

[0254] The first entity 1404 may receive a message or command requesting charging from the host intelligent charging receiver 1408. The second entity 1406 may receive a message or command requesting charging from the host intelligent charging receiver 1408. Authorized personnel of the first entity 1404 and the second entity 1406 may approve or reject the request. The message command may include charging requirements (i.e., the charging required by the host vehicle). Once the request is approved, the first intelligent charging receiver and the second intelligent charging receiver transfer power (e.g., the requested charging) to the host vehicle. In an embodiment, the host intelligent charging receiver may be configured to determine the charging status of the first entity 1404 and the second entity 1406, and transmit a message / command requesting charging to at least one of the first entity 1404 and the second entity 1406. The first entity 1404 may act as an extended charger based on the message / command. Similarly, the second entity 1406 may act as an extended charger based on the message / command. An extended charger is a charger that couples the host vehicle to another entity. The extended charger may disconnect the power of one of its battery packs and transfer only the power from another entity to the host vehicle. In one embodiment, the extended charger may provide power from its own battery pack in addition to providing power from another entity to the host vehicle. In one embodiment, the second entity is coupled to the host vehicle through the first entity. In one embodiment, the first entity disconnects the first charging and provides the second charging to the host vehicle. In one embodiment, the first entity provides the first charging to the host vehicle in addition to providing the second charging to the host vehicle.

[0255] Once the connection is established, the system is operable to receive at least one of the first charging and the second charging from the first entity 1404 and the second entity 1406. The first charging is the power received from the first entity 1404, and the second charging is the power received from the second entity 1406. In one embodiment, the system is operable to receive the first charging and the second charging from the first entity 1404 and the second entity 1406 simultaneously through one or more adapters 1402, respectively. In another embodiment, the system is operable to combine the first charging and the second charging and provide the optimal charging based on at least one of the charging specifications and charging requirements of the host vehicle. In another embodiment, the system is operable to disconnect the first charging and provide the second charging as the optimal charging. The system may provide the optimal charging to one or more battery packs of the host vehicle by providing at least one of the first charging and the second charging.

[0256] In one embodiment, the system may provide the optimal charging for one or more first battery packs of the host vehicle according to the charging requirements, charging specifications, and charging costs. The artificial intelligence engine determines at least one of the itinerary, environmental conditions, and traffic conditions of the host vehicle, and transmits the fourth sensing information. Then, the processor determines the charging requirements of the host vehicle based on the fourth sensing information.

[0257] In one embodiment, the sensor module determines a parameter related to at least one of a state of health (SoH), a state of charge (SoC), a host vehicle temperature, and an ambient temperature and transmits third sensing information. The processor then determines a charging requirement of the host vehicle based on the third sensing information received from the sensor module.

[0258] In one embodiment, the processor is operable to determine a charging requirement of the host vehicle based on at least one of the third sensing information received from the sensor module and fourth sensing information received from an artificial intelligence engine. The fourth sensing information includes one of a trip of the host vehicle, ambient conditions, and traffic conditions.

[0259] In one embodiment, the charging requirement includes at least one of a charging sequence, a charging time, and a charging duration. The charging sequence includes at least one of level 1 charging, level 2 charging, and level 3 charging. Level 1 charging includes trickle charging. Level 2 charging includes normal charging. Level 3 charging includes fast charging. The charging time includes a combination of at least one of a first charging time period, a second charging time period, and a third charging time period. The charging sequence includes a combination of at least one of level 1 charging corresponding to the first charging time period, level 2 charging corresponding to the second charging time period, and level 3 charging corresponding to the third charging time period.

[0260] In one embodiment, the first charging received from a first entity includes one of level 1 charging, level 2 charging, and level 3 charging. In another embodiment, the second charging received from a second entity includes one of level 1 charging, level 2 charging, and level 3 charging.

[0261] In one embodiment, the charging sequence includes a combination of at least one of level 1 charging corresponding to a first portion of one or more first battery packs, level 2 charging corresponding to a second portion of one or more first battery packs, and level 3 charging corresponding to a third portion of one or more first battery packs.

[0262] In one embodiment, the processor 1410 is operable to automatically provide optimal charging to one or more first battery packs of the host vehicle based on at least one of a charging specification, a charging requirement, and a charging cost of the host vehicle. In another embodiment, the processor 1410 is operable to receive user input and provide optimal charging to one or more first battery packs of the host vehicle based on the user input. In one embodiment, the processor 1410 enables a user to provide user input by selecting one of dropdown menus via one of a vehicle computer system and an external device. In one embodiment, the external device includes one of a smart phone, a tablet computer, a computer, a desktop computer, a tablet computer, a handheld device, and a smart watch. The dropdown menu includes options for one of a charging specification, a charging requirement, and a charging cost of the host vehicle.

[0263] In one embodiment, the artificial intelligence engine is operable to analyze a first charge and a second charge and determine a predefined first charge and a predefined second charge obtained from a first entity and a second entity, respectively. The artificial intelligence engine is then operable to determine the predefined first charge and the predefined second charge obtained from the first entity 1404 and the second entity 1406 based on the charging requirements of the host vehicle. The host intelligent charge receiver 1408 is operable to receive the predefined first charge and the predefined second charge from the first entity 1404 and the second entity 1406, respectively.

[0264] As an example, Figure 15 Displays a method according to one or more embodiments. The method includes: determining the presence of one or more adapters electrically coupled to the host vehicle (at step 1503); identifying at least one of a first entity and a second entity electrically coupled to the host vehicle through the one or more adapters (at step 1505); establishing a connection between the host vehicle, the first entity, and the second entity (at step 1507); transmitting a command to one of the first entity and the second entity to act as an extension cord based on a first charge and a second charge received from the first entity and the second entity, respectively (at step 1509); and providing an optimal charge to one or more first battery packs of the host vehicle by providing at least one of the first charge and the second charge (at step 1511).

[0265] In one embodiment, the method further includes: capturing one of one or more images and one or more videos of at least one of the host vehicle, the first entity, and the second entity and transmitting fifth sensing information. The method further includes: identifying the identity of at least one of the host vehicle, the first entity, and the second entity based on the fifth sensing information received from the sensor module. The method further includes: analyzing one of one or more images and one or more videos of at least one of the host vehicle, the first entity, and the second entity and identifying the identity of at least one of the host vehicle, the first entity, and the second entity by performing image analysis.

[0266] In one embodiment, the method further includes: determining the charging requirements of the host vehicle based on fourth sensing information. The method further includes: determining at least one of the travel, environmental conditions, and traffic conditions of the host vehicle by the artificial intelligence engine and communicating the fourth sensing information.

[0267] In one embodiment, the method further includes: identifying at least one of a first entity and a second entity electrically coupled to the host vehicle through one or more adapters based on at least one of one or more images and one or more videos captured by the sensor module. The method further includes: analyzing at least one of one or more images and one or more videos captured by the sensor module and extracting meaningful information by the artificial intelligence engine to identify at least one of the first entity and the second entity.

[0268] In one embodiment, the method further includes: receiving a first charge and a second charge from a first entity and a second entity respectively through one or more adapters simultaneously. The method further includes: combining the first charge and the second charge and providing an optimal charge based on at least one of the charging specifications and charging requirements of the host vehicle. In one embodiment, the method further includes: disconnecting the first charge and providing the second charge as the optimal charger.

[0269] In one embodiment, the method further includes: determining parameters related to at least one of state of health (SoH), state of charge (SoC), host vehicle temperature, and ambient temperature and transmitting third sensing information. The method further includes: determining the charging requirements of the host vehicle based on the third sensing information received from the sensor module.

[0270] In one embodiment, the method further includes: determining the charging requirements of the host vehicle based on at least one of the third sensing information received from the sensor module and the fourth sensing information received from the artificial intelligence engine, wherein the fourth sensing information includes one of the itinerary, environmental conditions, and traffic conditions of the host vehicle.

[0271] As an example, Figure 16 A non-transitory computer-readable medium is shown according to one or more embodiments. The non-transitory computer-readable medium stores a series of instructions that, when executed by a processor, cause: determining the presence of one or more adapters electrically coupled to the host vehicle (at step 1603); identifying at least one of a first entity and a second entity electrically coupled to the host vehicle through one or more adapters (at step 1605); establishing a connection between the host vehicle, the first entity, and the second entity (at step 1607); transmitting a command to one of the first entity and the second entity to be used as an extension cord based on the first charge and the second charge received from the first entity and the second entity respectively (at step 1609); and providing an optimal charge to one or more first battery packs of the host vehicle by providing at least one of the first charge and the second charge (at step 1611).

[0272] In one embodiment, the non-transitory computer-readable medium further performs: determining at least one of the itinerary, environmental conditions, and traffic conditions of the host vehicle through an artificial intelligence engine and communicating the fourth sensing information.

[0273] In one embodiment, the non-transitory computer-readable medium further causes: determining the charging requirements of the host vehicle based on the fourth sensing information.

[0274] In one embodiment, the non-transitory computer-readable medium further causes: identifying at least one of a first entity and a second entity electrically coupled to a host vehicle via one or more adapters based on at least one of one or more images and one or more videos captured by a sensor module.

[0275] In one embodiment, the non-transitory computer-readable medium further causes: analyzing at least one of one or more images and one or more videos captured by a sensor module and extracting meaningful information via an artificial intelligence engine to identify at least one of the first entity and the second entity.

[0276] In one embodiment, the non-transitory computer-readable medium further causes: receiving a first charge and a second charge from the first entity and the second entity simultaneously via one or more adapters.

[0277] In one embodiment, the non-transitory computer-readable medium further causes: combining the first charge and the second charge and providing it as an optimal charge based on the charging specification of the host vehicle.

[0278] In one embodiment, the non-transitory computer-readable medium further causes: bypassing the first charge and providing the second charge as the optimal charge.

[0279] In one embodiment, the non-transitory computer-readable medium further causes: determining the charging requirement of the host vehicle based on third sensing information received from the sensor module.

[0280] In one embodiment, the non-transitory computer-readable medium further causes: determining parameters related to at least one of state of health (SoH), state of charge (SoC), host vehicle temperature, and ambient temperature and communicating the third sensing information.

[0281] In one embodiment, the non-transitory computer-readable medium further causes: determining the charging requirement of the host vehicle based on at least one of the third sensing information received from the sensor module and the fourth sensing information received from the artificial intelligence engine, wherein the fourth sensing information includes one of the travel, ambient conditions, and traffic conditions of the host vehicle.

[0282] As an example, Figure 17 Messages sent by a host intelligent charge receiver to a first entity according to one or more embodiments are shown. In an embodiment, the message is similar to the HL7 protocol. Figure 17 The example message shown includes fields such as host vehicle ID, pairing ID, charging time, charging duration, charging sequence, state of charge (SoC), state of health, extended charge, intermediate function, etc. The first entity here may be a vehicle.

[0283] The vehicle ID can be a serial identification number or a tag associated with the electric vehicle, which is configured to identify and locate the electric vehicle. The pairing ID can be identification information communicated between two components for authentication and seamless information transfer between the components. The charging time can be a predetermined time, i.e., the allocated time, for optimal charging of the host vehicle. The charging duration refers to the duration (i.e., time period) of charging the electric vehicle. The state of health refers to the health state information of different parts of the battery pack of the host vehicle. The charging state refers to the charging state information of different parts of the battery pack of the host vehicle. Extended charging means that in addition to the charging received from the second entity, charging is also provided by the first entity. Extended charging can also refer to only providing the second charging received from the second entity. The extended charging field can have an attribute of "yes" or "no". If it is "yes", the host vehicle can receive charging from the first entity in addition to the charging received from the second entity. If "no", the host vehicle can only receive charging from the first entity or the second entity. The first entity decodes and extracts the information for charging the host vehicle after receiving the message. Then, the first intelligent charging receiver in the first entity can supply power according to the information received through the message to charge the host vehicle in an optimal manner. The mediation function refers to designating an entity as a mediation entity that can act as an extended charger.

[0284] As an example, Figure 18 Fig. shows a message sent by a host intelligent charging receiver to a first entity according to one or more embodiments. In an embodiment, the message is similar to the HL7 protocol. Figure 18 The example message shown includes fields such as host vehicle ID, pairing ID, charging time, charging duration, charging sequence, state of charge (SoC), state of health, extended charging, mediation function, etc. The first entity in this article can be a charging station.

[0285] The vehicle ID can be a serial identification number or a tag associated with the electric vehicle, which is configured to identify and locate the electric vehicle. The pairing ID can be identification information for communication between two components, used for authentication and seamless information transmission between the components. The charging time can be a predetermined time, i.e., the allocated time, for optimally charging the vehicle. The charging duration refers to the duration (i.e., time period) for charging the electric vehicle. The charging sequence refers to the charging mode defined by the host intelligent charging receiver based on battery parameters (e.g., state of charge, state of health). The state of health refers to the health state information of different parts of the battery pack. The state of charge refers to the charge state information of different parts of the battery pack. Extended charging means that, in addition to the charging received from the second entity, charging is also provided by the first entity. The extended charging field can have an attribute of "yes" or "no". If it is "yes", the host vehicle can receive charging from the first entity in addition to the charging received from the second entity. If it is "no", the host vehicle can receive charging only from the first entity or the second entity. In one embodiment, the first entity can disconnect the first charging and connect only the second charging. The first entity decodes and extracts the information for charging the vehicle after receiving the message. Then, the first intelligent charging receiver in the first entity can supply power according to the information received through the message to optimally charge the host vehicle.

[0286] As an example, Figure 19 Illustrates that, according to one or more embodiments, the first entity serves as an extended charger. The host vehicle can be connected to the first entity and the second entity. The first entity can be an intermediate entity. The host vehicle includes a host intelligent charging receiver. The first entity can include a first intelligent charging receiver. The second entity can include a second intelligent charging receiver. In this embodiment, the host intelligent charging receiver receives only the second charging from the second entity. The host intelligent charging receiver disconnects the power supply from the first entity to the host vehicle. Here, the first entity serves as an extended charger. In one embodiment, the host vehicle is connected to the second entity through the first entity.

[0287] As an example, Figure 20 Illustrates the first entity serving as an extended charger according to one or more embodiments. The host vehicle can be connected to the first entity and the second entity. The first entity can be an intermediate entity. The host vehicle includes a host intelligent charging receiver. The first entity can include a first intelligent charging receiver. The second entity can include a second intelligent charging receiver. In this embodiment, the host intelligent charging receiver receives the first charging and the second charging for the host vehicle. In one embodiment, the host vehicle is connected to the second entity through the first entity.

[0288] As an example, Figure 21Illustrated according to one or more embodiments, a first entity serves as an extended charger. A host vehicle may be connected to the first entity and the second entity. The first entity may be an intermediate entity. The host vehicle includes a host intelligent charging receiver. The first entity may include a first intelligent charging receiver. The second entity may include a second intelligent charging receiver. In this embodiment, the host intelligent charging receiver only receives the first charge from the first entity. The host intelligent charging receiver disconnects the second entity from powering the host vehicle. Here, the first entity serves as an extended charger.

[0289] In one embodiment, the system further includes a network security module, wherein the network security module includes an information security management module that provides isolation between the communication module and the server.

[0290] In one embodiment, the information security management module is operable to receive data from the communication module, exchange security keys when starting communication between the communication module and the server, receive a security key from the server, verify the identity of the server by verifying the security key, analyze whether there is a potential network security threat in the security key, negotiate an encryption key between the communication module and the server, encrypt the data; and transmit the encrypted data to the server when no network security threat is detected.

[0291] In one embodiment, the information security management module is operable to exchange security keys when starting communication between the communication module and the server, receive a security key from the server, authenticate the identity of the server by verifying the security key, analyze whether there is a potential network security threat in the security key, negotiate an encryption key between the system and the server, receive encrypted data from the server, decrypt the encrypted data, perform an integrity check on the decrypted data, and transmit the decrypted data to the communication module when no network security threat is detected.

[0292] In one embodiment, the system may include a network security module.

[0293] In one aspect, a secure communication management (SCM) computer device for providing a secure data connection is provided. The SCM computer device includes a processor in communication with a memory. The processor is programmed to receive a first data message from a first device. The first data message is in a standardized data format. The processor is further programmed to analyze whether there is a potential network security threat in the first data message. If it is determined that the first data message does not contain a network security threat, the processor is further programmed to convert the first data message into a first data format associated with the vehicle environment and transmit the converted first data message to the vehicle system using a first communication protocol associated with the vehicle system.

[0294] According to one embodiment, the secure authentication of data transmission includes: configuring a hardware-based security engine (HSE) located in a communication system, the HSE being manufactured in a secure environment and authenticated as part of an approved network in the secure environment; using the HSE to perform asynchronous authentication, verification, and encryption of data, storing user privilege data and connection status data in an access control list for defining an allowable data communication path of the approved network, enabling the communication system to communicate with other computing systems constrained by the access control list, and using the security engine to perform asynchronous verification and encryption of data, including identifying a user device (UD) equipped with one or more hardware-based modules for protecting security aspects of the system and embodying credentials in the hardware, where the security aspects include hardware-based modules for communicating with the user of the user device and the HSE.

[0295] In one embodiment, Figure 22A A block diagram showing a network security module is presented. Data transmission between system 2200 and server 2270 via communication module 2212 is first verified by information security management module 2232 before being transmitted from the system to the server or from the server to the system. The information security management module is operable to analyze whether there are potential network security threats in the data, encrypt the data when no network security threats are detected, and transmit the encrypted data to the system or the server.

[0296] In one embodiment, the network security module further includes an information security management module for providing isolation between the system and the server. Figure 22B A flowchart showing the protection of data by network security module 2230 is presented. At step 2240, the information security management module is operable to receive data from the communication module. At step 2241, the information security management module exchanges security keys at the start of communication between the communication module and the server. At step 2242, the information security management module receives a security key from the server. At step 2243, the information security management module verifies the identity of the server by verifying the security key. At step 2244, the information security management module analyzes whether there are potential network security threats in the security key. At step 2245, the information security management module negotiates an encryption key between the communication module and the server. At step 2246, the information security management module receives encrypted data. At step 2247, when no network security threats are detected, the information security management module transmits the encrypted data to the server.

[0297] In one embodiment, Figure 22CA flowchart showing the protection of data by the network security module 2230. At step 2251, the information security management module is operable to: exchange security keys at the start of communication between the communication module and the server. At step 2252, the information security management module receives a security key from the server. At step 2253, the information security management module verifies the identity of the server by validating the security key. At step 2254, the information security management module analyzes whether there are potential cybersecurity threats in the security key. At step 2255, the information security management module negotiates an encryption key between the communication module and the server. At step 2256, the information security management module receives encrypted data. At step 2257, the information security management module decrypts the encrypted data and performs an integrity check on the decrypted data. At step 2258, when no cybersecurity threat is detected, the information security management module transmits the decrypted data to the communication module.

[0298] In one embodiment, the integrity check is a hash signature verification using the Secure Hash Algorithm 256 (SHA256) or a similar method.

[0299] In one embodiment, the information security management module is configured to perform asynchronous authentication and verification of the communication between the communication module and the server.

[0300] In one embodiment, the information security management module is configured to issue an alert if a cybersecurity threat is detected. In one embodiment, the information security management module is configured to discard the received encrypted data if the integrity check of the encrypted data fails.

[0301] In one embodiment, the information security management module is configured to check the integrity of the decrypted data by checking accuracy, consistency, and any possible data loss during communication through the communication module.

[0302] In one embodiment, the server is physically isolated from the system by the information security management module. When the system is as Figure 22AWhen communicating with the server, first authenticate the system and the server. The system is responsible for transmitting / exchanging the public key of the system and the signature of the public key with the server. The public key of the system and the signature of the public key are sent to the information security management module. The information security management module decrypts the signature and verifies whether the decrypted public key is the same as the original public key received. If the verification passes, the authentication is successful. Similarly, the system and the server authenticate the information security management module. After the authentication is passed to the information security management module, the two communicating parties (the system and the server) negotiate the encryption key and the integrity check key for data communication through the authenticated asymmetric key. The session ID number is transmitted during the authentication process, so the key needs to be bound to the session ID number. When the system sends data outward, the information security gateway receives the data through the communication module, verifies the integrity of the data, then encrypts the data with the negotiated key, and finally transmits the data to the server through the communication module. When the information security management module receives the data through the communication module, it first decrypts the data, and then verifies the integrity of the data after decryption. If the verification passes, the data is sent out through the communication module; otherwise, the data is discarded.

[0303] In one embodiment, the authentication is implemented using signed asymmetric keys.

[0304] In one embodiment, the signature is implemented by a pair of asymmetric keys trusted by the information security management module and the system. The private key is used to sign the identities of the two communicating parties, and the public key is used to verify whether the identities of the two communicating parties are signed. The signed identity consists of a pair of public keys and a pair of private keys. In other words, the signed identity is the common name of the certificate installed on the user machine.

[0305] In one embodiment, both communicating parties need to authenticate their identities through a pair of asymmetric keys and identify the task responsible for communicating with the system information security management module through a unique pair of asymmetric keys.

[0306] In one embodiment, the dynamic key negotiation uses the RSA (Rivest-Shamir-Adleman) encryption algorithm for encryption. RSA is a public key cryptosystem widely used for secure data transmission. The negotiated key includes the data encryption key and the data integrity check key.

[0307] In one embodiment, the data encryption method is the triple data encryption algorithm (3DES). The integrity verification algorithm is the hashed message authentication code (HMAC-MD5-128) algorithm. When outputting data, integrity verification calculation is performed on the data, the calculated message authentication code (MAC) value is added to the header of the value data message, and then the 3DES algorithm is used to encrypt the data (including the MAC in the header). After encryption, the header information of the security layer is added, and then the data is sent to the next layer for processing. In one embodiment, the next layer refers to the transport layer in the Transmission Control Protocol / Internet Protocol (TCP / IP) model.

[0308] The information security management module ensures the security, reliability, and confidentiality of the communication between the system and the server through the authentication of the identities of both communication parties when starting data encryption and data integrity authentication. It is particularly suitable for embedded platforms with less resources and not connected to the PKI system. By ensuring the security and reliability of the communication between the system and the server, it can ensure the security of the data on the server from being harmed by hacker attacks in the Internet situation.

[0309] In one embodiment of the system, the machine learning model is configured to learn using labeled data with a supervised learning method, where the supervised learning method includes the logic of performing regression using at least one of decision tree, logistic regression, support vector machine, k-nearest neighbor, naive Bayes, random forest, linear regression, polynomial regression, and support vector machine.

[0310] In one embodiment of the system, the machine learning model is configured to learn from real-time data with an unsupervised learning method, where the unsupervised learning method includes the logic of using at least one of k-means clustering, hierarchical clustering, hidden Markov model, and apriori algorithm.

[0311] In one embodiment of the system, the machine learning model has a feedback loop, where the output of the previous step is fed back to the model in real time to improve the performance and accuracy of the next step output.

[0312] In one embodiment of the system, the machine learning model includes a recurrent neural network model.

[0313] In one embodiment of the system, the machine learning model has a feedback loop, where further reinforcement learning is performed through the reward for each true positive of the system output.

[0314] Figure 23AShows the structure of a neural network / machine learning model with a feedback loop. An artificial neural network (ANN) model includes an input layer, one or more hidden layers, and an output layer. Each node or artificial neuron is connected to another node and has an associated weight and threshold. If the output of any single node is higher than the specified threshold, the node is activated and data is sent to the next layer of the network. Otherwise, no data is passed to the next layer of the network. A machine learning model or ANN model can be trained on a set of data, accept requests in the form of input data, make predictions on the input data, and then provide a response. The model can learn from the data. The learning can be supervised learning and / or unsupervised learning and can be based on different scenarios and different data sets. Supervised learning includes the logic of using at least one of decision trees, logistic regression, and support vector machines. Unsupervised learning includes the logic of using at least one of k-means clustering, hierarchical clustering, hidden Markov models, and apriori algorithms. The output layer can predict or detect the charging requirements and the charging entity for charging the host vehicle based on the input data.

[0315] In one embodiment, the ANN can be a deep neural network (DNN), which is a multi-layer cascaded neural network, including an artificial neural network (ANN), a convolutional neural network (CNN), and a recurrent neural network (RNN), which can identify the features of the input, conduct expert reviews, and perform operations that require prediction, creative thinking, and analysis. In one embodiment, the ANN can be a recurrent neural network (RNN), which is a type of artificial neural network (ANN) that uses sequential data or time series data. Deep learning algorithms are typically used for ordinal or time problems, such as language translation, natural language processing (NLP), speech recognition, and image recognition, etc. Like feedforward and convolutional neural networks (CNNs), recurrent neural networks learn using training data. They are characterized by "memory" because they obtain information from previous inputs through a feedback loop to affect the current input and output. The output of the output layer in the neural network model is fed back to the model through feedback. When training the model, the changes in the weights of the hidden layer will be adjusted to better fit the expected output. This will enable the model to provide results with fewer errors.

[0316] The neural network has a feedback loop that can dynamically adjust the system output when learning from new data. In machine learning, backpropagation and feedback loops are used to train AI models and continuously improve them during use. As the amount of incoming data received by the model increases, the opportunities for the model to learn from the data also increase. The feedback loop or backpropagation algorithm can identify inconsistencies and feed the corrected information back into the model as input.

[0317] Even if an AI / ML model is well-trained with a large amount of labeled data and concepts, after some time, due to many reasons, the performance of the model may degrade when new unlabeled inputs are added. These reasons include, but are not limited to, concept drift, recall-precision degradation due to deviation from true positives, and data drift over time. The feedback loop of the model can maintain the accuracy of the AI results and ensure that the model maintains its performance and improves, even when absorbing new unlabeled data. A feedback loop is the process of reusing the predicted output of an AI model to train a new version of the model.

[0318] Initially, when training an AI / ML model, some labeled samples are used, which contain both positive and negative examples of a concept (e.g., charging requirements) for the model to learn. After that, the model is tested using unlabeled data. Through the use of deep learning and neural networks, etc., the model can predict whether the desired concepts (e.g., charging requirements and the entities used for charging) exist in the unlabeled images. Each image is assigned a probability score, and the higher the score, the higher the confidence of the model's prediction. If the model assigns a high probability score to an image, the image is automatically labeled with the predicted concept. However, in the case where the model returns a low probability score, the input may be sent to a controller (possibly a human mediator), who will verify the result and correct it if necessary. Human mediators are only used in exceptional cases. The feedback loop dynamically feeds the labeled data (automatically labeled or controller-verified) back to the model and uses it as training data so that the system can dynamically improve its predictions in real time.

[0319] Figure 23B Shows the structure of a neural network / machine learning model with reinforcement learning. The network receives feedback from an authorized network environment. Although the system is similar to supervised learning, the feedback obtained in this case is evaluative rather than instructive, which means there is no teacher like in supervised learning. After receiving the feedback, the network adjusts its weights to obtain better predictions in the future. Machine learning techniques (such as deep learning) allow the model to obtain labeled training data and learn to identify these concepts in subsequent data and images. The model can be input with new data for testing, so the training is strengthened by inputting the data that has already been predicted to the model. If the machine learning model has a feedback loop, the learning is further strengthened by rewarding each true positive of the system output. The feedback loop ensures that the AI results do not stagnate. By incorporating the feedback loop, the model output continuously improves dynamically over time / with use.

[0320] The embodiments described herein include only examples of systems and computer-implemented methods. Of course, in order to describe one or more embodiments, it is not possible to describe all conceivable combinations of components and / or computer-implemented methods, but those of ordinary skill in the art will recognize that many further combinations and / or permutations of one or more embodiments are possible. Additionally, to the extent that the terms "including," "having," "possessing," etc. are used in the detailed description, claims, appendices, and / or drawings, these terms are intended to be inclusive in a manner similar to the term "comprising," as "comprising" is interpreted to be inclusive when used as a transitional word in the claims.

[0321] The present invention may also be embodied in other specific forms without departing from the spirit or characteristics of the invention. The embodiments are illustrative rather than restrictive in all respects. Accordingly, the scope of the invention is indicated by the appended claims rather than the description herein. All changes that come within the meaning and range of equivalency of the claims are embraced within their scope.

Claims

1. A system, comprising: One or more adapters; A first entity; A second entity; And A host intelligent charging receiver, comprising: A processor storing instructions in non-transitory memory, the instructions when executed causing the processor to: Determine the presence of one or more adapters electrically coupled to a host vehicle; Identify at least one of a first entity and a second entity electrically coupled to the host vehicle via the one or more adapters; Establish a connection between the host vehicle, the first entity, and the second entity; Based on a first charge and a second charge received from the first entity and the second entity respectively, Convey a command to one of the first entity and the second entity to act as an extended charger; and Provide optimal charging for one or more first battery packs of the host vehicle by providing at least one of the first charge and the second charge.

2. The system according to claim 1, wherein the first entity includes one of a vehicle, a charging station, and a solar panel station.

3. The system according to claim 1, wherein the second entity includes one of a vehicle, a charging station, and a solar panel station.

4. The system according to claim 1, wherein the first entity and the second entity are similar entities.

5. The system according to claim 1, wherein the first entity and the second entity are different entities.

6. The system according to claim 1, wherein the one or more adapters are extended by electrically coupling one or more subsequent adapters to receive input power from subsequent entities.

7. The system according to claim 1, wherein the host intelligent charging receiver includes an artificial intelligence engine.

8. The system according to claim 7, wherein the processor is operable to determine the charging requirements of the host vehicle based on one of the itinerary of the host vehicle, environmental conditions, and traffic conditions.

9. The system according to claim 1, wherein the system further includes a sensor module.

10. The system according to claim 1, wherein the second entity is coupled to the host vehicle via the first entity.

11. The system according to claim 10, wherein the first entity disconnects the first charge and provides the second charge to the host vehicle.

12. The system according to claim 10, wherein the first entity provides the first charge to the host vehicle in addition to providing the second charge to the host vehicle.

13. The system according to claim 1, wherein the connection between the host vehicle, the first entity, and the second entity is a daisy chain connection.

14. A method, comprising: Determine the presence of one or more adapters electrically coupled to a host vehicle; Identify at least one of a first entity and a second entity electrically coupled to the host vehicle via one or more adapters; Establish a connection between the host vehicle, the first entity, and the second entity; Based on a first charge and a second charge received from the first entity and the second entity respectively, convey a command to one of the first entity and the second entity to cause it to act as an extended charger; And Provide optimal charging for one or more first battery packs of the host vehicle by providing at least one of the first charge and the second charge.

15. The method according to claim 14, further comprising: Receiving a first charge from a first entity and a second charge from a second entity simultaneously via the one or more adapters.

16. The method according to claim 15, further comprising: Combining the first charge and the second charge and providing an optimal charge based on at least one of the charging specifications and charging requirements of the host vehicle.

17. The method according to claim 15, further comprising: Disconnecting the first charge and providing the second charge as the optimal charge.

18. A non-transitory computer-readable medium storing a series of instructions that, when executed by a processor, cause: Determining the presence of one or more adapters electrically coupled to a host vehicle; Identifying at least one of a first entity and a second entity electrically coupled to the host vehicle via the one or more adapters; Establishing a connection between the host vehicle, the first entity, and the second entity; Based on a first charge and a second charge received from the first entity and the second entity respectively, communicating a command to one of the first entity and the second entity to act as an extended charger; And Providing an optimal charge to one or more first battery packs of the host vehicle by providing at least one of the first charge and the second charge.

19. The non-transitory computer-readable medium according to claim 18, further causing: Determining the charging requirements of the host vehicle based on third sensing information received from a sensor module.

20. The non-transitory computer-readable medium according to claim 19, further causing: Determining parameters related to at least one of state of health (SoH), state of charge (SoC), host vehicle temperature, and ambient temperature and communicating the third sensing information.

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