System and apparatus for positioning available chargers

Abstract

A system is described. The system comprises a sensor module and a control module. The control module comprises a processor and a memory. The memory includes a sensor control module that, when executed by the processor, causes the processor to: determine a first state of charge of one or more batteries of the vehicle; determining whether the first state of charge is below a threshold charge level; determining one or more first geographic ranges including one or more first charging stations based on the first state of charge; determining charge consumption factors affecting charge consumption in the battery; estimating charge consumption based on the charge consumption factor; determining a second state of charge based on the charge consumption; determining one or more second geographic ranges including one or more second charging stations based on the second state of charge; and reserving one or more charging sessions with one or more second charging stations to charge the battery.

Description

Technical Field

[0001] The present disclosure generally relates to a charging system for an electric vehicle. More specifically, the present disclosure relates to a system and method for locating and reserving available charging stations / chargers. Background Art

[0002] Current charging systems are not the best option for charging and do not have an efficient reservation system. For example, when a driver wants to charge a vehicle, the driver does not know whether there is a charger available for charging, whether it is for short-term charging or long-term charging. In the case where the state of charge is below a threshold and there is no available charger, the driver will be in a difficult situation. Therefore, an automatic reservation system is needed to ensure that when the state of charge is below the threshold, the system will automatically find an available charger and reserve the charger.

[0003] Therefore, there has long been a need for a system and method for locating and reserving available charging stations / chargers. Summary of the Invention

[0004] The following summary provides a basic understanding of one or more embodiments of the present invention. The summary is not intended to identify important or key elements, or to describe any scope of a particular embodiment or any scope of the claims. Its sole purpose is to present concepts in a simplified form as a prelude to the more detailed description presented later.

[0005] In one or more embodiments described herein, a system, device, computer-implemented method, method, apparatus, and / or computer program product are provided that facilitate locating and reserving available charging stations / chargers.

[0006] In one aspect, a system is described that includes: a sensor module; and a control module. The control module includes a processor; and a memory communicatively coupled to the processor. The memory includes a sensor control module that, when executed by the processor, causes the processor to: determine a first state of charge of one or more batteries associated with a vehicle; determine whether the first state of charge is below a threshold state of charge; determine one or more geographical ranges including one or more first charging stations based on the first state of charge; determine one or more charge consumption factors that affect charge consumption in the one or more batteries; estimate charge consumption based on the one or more charge consumption factors; determine a second state of charge based on the charge consumption; determine a remaining time of the vehicle based on the second state of charge; calculate one or more charging sessions using an artificial intelligence engine based on at least one of an arrival time, a charging duration, and the remaining time; and based on the one or more charging sessions

[0007] In one aspect, a method is described that includes: determining a first state of charge of one or more batteries associated with a vehicle; determining whether the first state of charge is below a threshold state of charge level; determining, based on the first state of charge, one or more first geographical ranges that include one or more first charging stations; determining one or more charge consumption factors that affect charge consumption in the one or more batteries; estimating charge consumption based on the one or more charge consumption factors; determining a second state of charge based on the charge consumption; determining, based on the second state of charge, one or more second geographical ranges that include one or more second charging stations; and scheduling one or more charging sessions with the one or more second charging stations to charge the one or more batteries.

[0008] In another aspect, a non-transitory computer-readable storage medium is described that includes a series of instructions that, when executed by a processor, cause: determining a first state of charge of one or more batteries associated with a vehicle; determining whether the first state of charge is below a threshold state of charge level; determining, based on the first state of charge, one or more first geographical ranges that include one or more first charging stations; determining one or more charge consumption factors that affect charge consumption in the one or more batteries; estimating charge consumption based on the one or more charge consumption factors; determining a second state of charge based on the charge consumption; determining, based on the second state of charge, one or more second geographical ranges that include one or more second charging stations; and scheduling one or more charging sessions with the one or more second charging stations to charge one or more batteries.

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

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

[0011] Figure 1 A block diagram of a system according to one or more embodiments is shown.

[0012] Figure 2 A method of scheduling a charging session according to one or more embodiments is shown.

[0013] Figure 3 A non-transitory computer-readable storage medium according to one or more embodiments is shown.

[0014] Figure 4Shows a block diagram for charging a vehicle according to one or more embodiments.

[0015] Figure 5 Shows a battery pack including a single battery according to one or more embodiments.

[0016] Figure 6 Shows a battery pack including multiple batteries according to one or more embodiments.

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

[0018] Figure 8a Shows one or more first geographical ranges according to one or more embodiments.

[0019] Figure 8b Shows one or more second geographical ranges according to one or more embodiments.

[0020] Figure 9a Shows a complete overlap of the first geographical range and the second geographical range according to one or more embodiments.

[0021] Figure 9b Shows that the second geographical range covers a part of the first geographical range according to one or more embodiments.

[0022] Figure 9c Shows the second geographical range and the first geographical range that are different from each other according to one or more embodiments.

[0023] Figure 10 Shows a schematic diagram of a charging station according to one or more embodiments.

[0024] Figure 11 Shows a message transmitted to the charging station described in Figure 1 according to one or more embodiments.

[0025] Figure 12 Shows a system for automatically connecting to and disconnecting from a charging station according to one or more embodiments.

[0026] Figure 13 Shows a method for automatically connecting to and disconnecting from a charging station according to one or more embodiments.

[0027] Figure 14 Shows a non-transitory computer-readable storage medium according to one or more embodiments.

[0028] Figure 15Shows the process of a robotic arm inserting a charger into a vehicle's charging port and removing the charger from the vehicle's charging port according to one or more embodiments.

[0029] Figure 16a Shows a first message according to one or more embodiments.

[0030] Figure 16b Shows a fourth message according to one or more embodiments.

[0031] Figure 17a Shows a second message according to one or more embodiments.

[0032] Figure 17b Shows a third message according to one or more embodiments.

[0033] Figure 18 Shows a vehicle scan according to one or more embodiments. In one embodiment, the vehicle is approaching a reserved charging station.

[0034] Figure 19 Shows a vehicle that automatically connects and disconnects from a charging station according to one or more embodiments.

[0035] Figure 20 Shows a method according to one or more embodiments.

[0036] Figure 21 Shows a non-transitory computer-readable storage medium according to one or more embodiments.

[0037] Figure 22 Shows a system for automatically locating an available charger due to a parking space being blocked according to one or more embodiments.

[0038] Figure 23 Shows a method according to one or more embodiments.

[0039] Figure 24 Shows a non-transitory computer-readable storage medium according to one or more embodiments.

[0040] Figure 25 Shows according to one or more embodiments of Figure 22 the first message described in

[0041] Figure 26 Shows the determination of a subsequent charging station according to one or more embodiments.

[0042] Figure 27 Shows the determination of one or more areas including a charging station according to one or more embodiments.

[0043] Figure 28Shows one or more routes provided to a reservation charging station according to one or more embodiments.

[0044] Figure 29 Shows one or more routes provided to a subsequent charging station according to one or more embodiments.

[0045] Figure 30A Shows the structure of a neural network / machine learning model with a feedback loop.

[0046] Figure 30B Shows the structure of a neural network / machine learning model with reinforcement learning.

[0047] According to the accompanying drawings and the following detailed description, other features of the present embodiment will become apparent. Detailed Description

[0048] For simplicity and clarity of illustration, the drawings show the general manner of construction. The description and 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 figures represent the same elements.

[0049] 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.

[0050] Accordingly, the embodiments herein are not intended to be limiting in any generality or to 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.

[0051] 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.

[0052] 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".

[0053] 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. Additionally, any aspect or design described herein as "example" and / or "exemplary" is not necessarily preferred or superior to other aspects or designs, nor does it exclude equivalent exemplary structures and techniques known to those of ordinary skill in the art.

[0054] 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 sequence. These terms may be interchangeable where appropriate, e.g., embodiments herein may operate in an order other than the order shown or otherwise described herein. Additionally, the terms "comprising", "having", and any variants thereof cover non-exclusive inclusion, so a process, method, system, article, device, or apparatus that includes 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.

[0055] 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 interchangeable such that embodiments of the devices, methods, and / or articles described herein can operate, for example, in an orientation different from the orientation shown or otherwise described herein.

[0056] Unless explicitly stated, any element, act, 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". The term "one" or similar language is used if only referring to a single item. Additionally, the terms "having", "possessing", "owning", etc. are open-ended terms. Additionally, the phrase "based on" means "at least partially based on" unless otherwise explicitly stated.

[0057] As used herein, the terms "system", "device", "unit", and / or "module" refer to different components, component parts, or levels of components in an order. However, these terms may be replaced by other expressions that achieve the same purpose.

[0058] As used herein, the term "coupled" means connecting two or more elements mechanically, electrically, and / or otherwise. Two or more electrical elements may be electrically coupled together, but not mechanically or otherwise coupled together. The 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" near words such as "coupled" does not mean that the coupling or the like being discussed is or is not detachable.

[0059] As used herein, the term "or" means inclusive "or" rather than exclusive "or". Unless otherwise stated or the context clearly dictates, "X employs A or B" means 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.

[0060] 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.

[0061] 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 can 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" can represent real-time minus the time delay for processing (e.g., determining) and / or transmitting data. The specific time delay can 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 can be less than about one second, two seconds, five seconds, or ten seconds.

[0062] 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.

[0063] A digital electronic circuit, or computer software, firmware, or hardware, including the structures disclosed in this specification and their structural equivalents, or a combination 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 modules of computer program instructions 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 substance composition affecting a machine-readable propagated signal, or a combination of one or more of them. The term "computing system" encompasses all devices, apparatuses, and machines for processing data, for example, including programmable processors, computers, or multiple processors or computers. In addition to hardware, the device may also include code that creates an execution environment for the computer program being discussed, for example, code constituting processor firmware, a protocol stack, a database management system, an operating system, or a combination of one or more of them. A propagated signal is an artificially generated signal (for example, an electrical, optical, or electromagnetic signal generated by a machine) that encodes information for transmission to a suitable receiving device.

[0064] The actual specific control hardware or software code for implementing these systems and / or methods is not limited to these implementations. Therefore, any software and any hardware can implement these systems and / or methods based on the description herein without referring to specific software code.

[0065] 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 language or interpreted language. It can be deployed in any suitable form, including as a stand-alone program or as modules, components, subroutines, or other units suitable for use in 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 (for example, one or more scripts in a markup language document), in a single file dedicated to the relevant program, or in multiple coordinated files (for example, 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.

[0066] One or more programmable processors execute one or more computer programs to perform functions by operating on input data and generating output, executing the processes and logical flows described in this specification. The processes and logical flows may also be executed by special-purpose logic circuitry, and the apparatus may also be implemented as special-purpose logic circuitry, such as, but not limited to, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), system on a chip (SOC) systems, complex programmable logic devices (CPLDs), etc.

[0067] Processors suitable for the execution of a computer program include, by way of example, both general and special purpose microprocessors, and one or more processors of any appropriate 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 may 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, transfer data, or both, from one or more mass storage devices for storing data, such as magnetic disks, magneto-optical disks, optical disks, or solid state disks. However, the computer need not have such devices. In addition, another device, such as a mobile phone, personal digital assistant (PDA), mobile audio player, global positioning system (GPS) receiver, etc., may 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, including by way of example semiconductor storage devices (such as, erasable programmable read only memory (EPROM), electrically erasable programmable read only memory (EEPROM), and flash memory devices), magnetic disks (such as internal hard disks or removable disks), magneto-optical disks (such as compact disc read only memory (CDROM) disks, digital versatile disk read only memory (DVD-ROM) disks), and solid state disks. Special-purpose logic circuitry may supplement or be incorporated in the processor and memory.

[0068] For interaction with a user, the 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 may also provide interaction with the user. For example, feedback to the user may be any appropriate form of sensory feedback, such as visual feedback, auditory feedback, or tactile feedback; and the computer may receive input from the user in any appropriate form, including acoustic, speech, or tactile input.

[0069] A computing system that includes a backend component (e.g., a data server), or includes a middleware component (e.g., an application server), or includes a frontend component (e.g., a client computer having a graphical user interface or a web browser through which a 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. Digital data communication in any suitable form or medium (e.g., 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.

[0070] A computing system can include a client and a server. The client and the server are remote from each other and typically interact via 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.

[0071] Embodiments can include or utilize a special-purpose or general-purpose computer including computer hardware. Embodiments within the scope of the present invention can 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 can include at least two different types of computer-readable media: physical computer-readable storage media and transmission computer-readable media.

[0072] Although the embodiments described herein are referenced 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.

[0073] In addition, non-transitory machine-readable media and / or systems can embody the various operations, processes, and methods disclosed herein. Thus, the specification and the drawings are illustrative rather than restrictive.

[0074] A physical computer-readable storage medium includes RAM, ROM, EEPROM, CD-ROM, or other optical disk storage (such as 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, which can be accessed by a general-purpose or special-purpose computer.

[0075] 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 (wired, wireless, or a combination of wired and wireless) transfers or provides information to a computer, the computer properly views the connection as a transmission medium. A general-purpose or special-purpose computer accesses the transmission medium, which can include a network and / or a 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 above combinations, which enable the transfer of electronic data between computer systems and / or modules and / or other electronic devices. Additionally, upon arrival at various computer system components, program code in the form of computer-executable instructions or data structures can automatically transfer from the transmission computer-readable medium to the 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.

[0076] 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. Computer-executable instructions can 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 method acts, the features or acts do not limit the subject matter defined in the claims. Instead, the features and acts described herein are example forms for implementing the claims.

[0077] Although this specification contains many details, these details do not constitute a limitation on the disclosure or the scope of the claims, but rather a description of features of a particular implementation. Certain features described in this specification can be implemented in the context of a single implementation. Conversely, multiple implementations can implement the various features described herein, either individually or in any suitable sub-combination, in the context of a single implementation. Additionally, although the features described herein operate in certain combinations and are even initially claimed as such, in some cases, one or more features in the claimed combination can be excised from the combination, and the claimed combination may be directed to a sub-combination or a variant of a sub-combination.

[0078] Similarly, although operations are depicted in the figures 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 operations shown 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 as requiring such separation in all implementations, and it should be understood that the described program components and systems can be integrated in a single software product or packaged into multiple software products.

[0079] Although specific combinations of features are recited in the claims and / or specific 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 actions recited in the claims can be performed in a different order and still achieve the desired result. In fact, many of these features can 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.

[0080] Furthermore, a computer system including one or more processors and a computer-readable medium (e.g., computer memory) can implement these methods. Specifically, one or more processors execute computer-executable instructions stored in the computer memory to perform various functions (e.g., the actions described in the embodiments).

[0081] 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 (by a hardwired data link, a wireless data link, or a combination of hardwired and wireless data links) and both perform tasks. In a distributed system environment, program modules can be located in local and remote memory storage devices.

[0082] Unless otherwise noted, the following terms and phrases shall have the following meanings.

[0083] As used herein, the term "sensor module" refers to a unit that includes components or circuits in addition to sensors. The additional components or circuits make the sensor easy to use. The sensor module can be an integrated circuit that includes additional components and sensors suitable for the application. The sensor module can include one or more sensors that operate together functionally. For example, one or more cameras and one or more sensors within the sensor module are integrated with each other to determine charge consumption factors. The sensors within the sensor module operate in an integrated manner to monitor environmental conditions, the external environment, etc., to estimate and monitor charge consumption.

[0084] The term "control module" as used herein refers to a unit or system that makes all important decisions about the way it operates. The term "control module" refers to a component that is designed to ensure the integrated operation of all components of a vehicle.

[0085] As used herein, the term "charging system" refers to a device capable of charging a battery pack. The battery pack can include one or more batteries. The charging system is capable of charging the battery pack. The charging system is also capable of monitoring and controlling the battery pack. The charging system is also capable of calculating and monitoring battery parameters (e.g., battery impedance, battery resistance, battery temperature, state of charge, state of health, etc.). The charging system is communicatively coupled to a vehicle computer system. The charging system is also communicatively coupled to a charging station.

[0086] As used herein, the term "electric vehicle (EV)" refers to a motor 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 (e.g., a battery), which can be charged from an off-vehicle power source (e.g., residential or public electric 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 vehicle, an electric vehicle, an electric road vehicle (ERV), a plug-in vehicle (PV), a plug-in vehicle (xEV), etc., and xEV can be classified into a plug-in all-electric vehicle (BEV), a battery electric vehicle, a plug-in electric vehicle (PEV), a hybrid electric vehicle (HEV), a hybrid plug-in electric vehicle (HPEV), a plug-in hybrid electric vehicle (PHEV), etc.

[0087] 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 the power grid.

[0088] As used herein, the term "plug-in vehicle (PV)" refers to an electric vehicle that can be wirelessly charged through an electric vehicle supply equipment (EVSE) without using a physical plug or physical socket.

[0089] The term "heavy-duty vehicle (HD vehicle)" refers to any four-wheeled or more-wheeled vehicle as defined in 49 CFR 523.6 or 49 CFR 37.3 (for buses).

[0090] As used herein, the term "light-duty plug-in electric vehicle" refers to a three-wheeled or four-wheeled vehicle driven by an electric motor that draws current from a rechargeable battery or other energy source device, mainly used for public streets, roads, and highways, and having a gross vehicle weight rating of less than 4,545 kg.

[0091] As used herein, the term "state of health (SoH)" refers to a quality factor of the 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, taking into account battery aging. 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.

[0092] As used herein, the term "charging station" refers to 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 be used 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. Communication can be established through a wired connection or a wireless connection. The charging station is also capable of charging an electric vehicle through a wired connection or a wireless connection.

[0093] As used herein, the term "charging session" refers to an event that starts from the initiation of a refueling event (e.g., a charging event) by a user or a vehicle and ends when the user or the vehicle terminates the refueling event (e.g., the charging event). A charging session further refers to a charging event of a single electric vehicle during which a certain amount of energy is transferred to the electric vehicle, and the duration is measured from the time when the electric vehicle is physically inserted into the electric vehicle supply equipment to the time when the electric vehicle is physically removed from the electric vehicle supply equipment.

[0094] The term "optimized route" as used herein refers to a route to a destination that has the shortest driving distance and can be traveled by the vehicle with less traffic conditions and less time. An optimized route refers to a route on which the vehicle travels with lower fuel, battery power, and efficiency.

[0095] As used herein, the term "battery pack" refers to a group of any number of identical batteries or individual battery cells of a battery. A "battery pack" can 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.

[0096] The term "control unit" or "control module" or "electronic control unit" as used herein 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 charging unit to charge a battery pack according to charging requirements.

[0097] 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), and memories that execute one or more software or firmware programs, combinational logic circuits, and / or other suitable components that provide the said functions.

[0098] The term "vehicle computer system" as used herein refers to an embedded system in automotive electronics that controls one or more electrical systems or subsystems in a vehicle. The computer executes 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.

[0099] 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 an automobile 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 automotive electronics. In another example, the electronic control unit is wirelessly coupled to automotive electronics.

[0100] The term "infotainment system" or "infotainment unit" or "in-vehicle infotainment system" (IVI) as used herein refers to a combination of systems for providing entertainment and information. In one example, information can be delivered to the driver and passengers of a vehicle via an audio / video interface, control elements such as a touchscreen display, a button panel, 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, automotive sensor integration, a digital dashboard, etc.

[0101] 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 the charge level for a predefined charging time period. The charging sequence can also include the charge level for a predefined part of the battery pack (e.g., healthy battery, degraded battery). The charge level can include normal charging, fast charging, and trickle charging.

[0102] As used herein, the term "maximum charging" or "optimal charging" refers to the maximum rate at which a battery pack can be charged within a charging time without damaging the battery pack.

[0103] As used herein, the term "charging time" refers to the time allotted for charging. The charging time can be provided by the user. The charging time can also be determined by the charging station or the charging system. The charging time can be divided into charging time periods. Each charging time period can correspond to a different charge level. Each charging time period can correspond to charging a different part of the battery pack.

[0104] As used herein, the term "state of charge (SoC)" refers to the charge 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.

[0105] As used herein, the term "first state of charge (SoC)" refers to the charge level of a battery pack relative to its capacity at a specific point in time.

[0106] As used herein, the term "second state of charge (SoC)" refers to the charge level of a battery pack relative to its capacity at a later point in time. For example, the second state of charge (SoC) refers to the charge level after charge consumption based on one or more charge consumption factors.

[0107] 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 can be preset by a processor of a control module. The threshold charge level can be changed by the processor.

[0108] As used herein, the term "first geographic range" refers to a distance range calculated based on the first state of charge. The first geographic range can refer to the distance range that a vehicle can travel using the first state of charge. The first geographic range can include one or more regions. The one or more regions can be continuous. The first geographic range can include one or more regions around the vehicle.

[0109] As used herein, the term "second geographic range" refers to a distance range calculated based on the second state of charge. The second geographic range can refer to the distance range that a vehicle can travel after consuming electrical energy due to one or more charge consumption factors. The second geographic range can refer to the distance range that a vehicle can travel using the second state of charge. The second geographic range can include one or more regions. The one or more regions can be continuous. The second geographic range can include one or more regions around the vehicle.

[0110] As used herein, the term "two-way communication" refers to the data exchange between two components. In one example, the first component can be a vehicle, and the second component can be an infrastructure supported by hardware, software, and firmware systems. This communication is typically wireless. In another example, the first component can be a charging system, and the second component can be a charging station.

[0111] 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 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. 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 to improve the accuracy and performance of the model over time.

[0112] As used herein, the term "communication" refers to the transfer of information and / or data from one point to another. Communication can occur 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 that exchanges information or data using electrical signals, using any system, hardware, software, protocol, or format, regardless of whether the exchange occurs 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 transfer 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 source 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.). Additionally, 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) through a communication line or via a communication satellite through satellite communication. The emergency communication device is adapted to communicate with communication terminals including a road management department, a police station, a fire department, and a hospital via the communication network. The emergency communication device can also be online-connected to the communication terminals of relevant personnel or vehicles associated with the occupants or vehicles of the emergency reporting vehicle and the drivers or vehicles receiving services.

[0113] 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 message header, where the payload includes quantitative values of shared information and the message header includes a reference to the shared information. The message structure serves as an upper-level structure to accommodate any sub-protocol structures such as AMQP, MQTT, Zigbee, etc.

[0114] As used herein, the term "artificial intelligence unit" refers to any system that can sense its environment and take actions to maximize its goals. The artificial intelligence unit utilizes a variety of machine learning algorithms to enable the system to automatically improve through experience.

[0115] 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 an information sender, a communication channel or medium, and an information receiver.

[0116] As used herein, the term "artificial intelligence (AI)" refers to the intelligence demonstrated by machines, as opposed to the natural intelligence demonstrated by humans. AI research is defined as any system that can sense 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.

[0117] As used herein, the term "sensor control module" refers to an actuator and basic control logic that acts as a regulating device, a state-oriented device, or a combination operating as a single device.

[0118] As used herein, the term "charge consumption factor" refers to one or more factors that cause charge consumption. The charge consumption factor can also refer to one or more factors that cause charge consumption. The charge consumption factor can be at least one of an internal charge consumption factor and an external charge consumption factor. The charge consumption factor can refer to factors that may cause the consumption of electrical energy and electricity to exceed the actual available electrical energy and electricity (usually the available electrical energy and electricity of a vehicle). The actual electricity refers to the energy for operating a vehicle under normal conditions (such as normal environment, normal mode, etc.).

[0119] As used herein, the term "internal charge consumption factor" refers to one or more factors within the vehicle. The internal charge consumption factor may include at least one of vehicle weight, the health of one or more batteries, occupant weight, luggage weight, vehicle specifications, vehicle operation mode, and vehicle fuel operation mode.

[0120] As used herein, the term "external charge consumption factor" refers to one or more factors outside the vehicle. The external charge consumption factor includes at least one of environmental conditions, road surface conditions, the distance between the one or more first charging stations and the vehicle, traffic conditions, waiting time, and driving mode.

[0121] As used herein, the term "vehicle weight" refers to the actual weight of the vehicle when it is not carrying a load.

[0122] As used herein, the term "occupant weight" refers to the weight of one or more occupants in the vehicle.

[0123] As used herein, the term "luggage weight" refers to the weight of one or more pieces of luggage loaded on the vehicle.

[0124] As used herein, the term "vehicle specifications" refers to a detailed description of the vehicle. Vehicle specifications refer to information on the basic details of the vehicle. Vehicle specifications may include measurements, mechanical details, engine performance, vehicle operation mode, operation type, load capacity, vehicle fuel operation mode, etc.

[0125] As used herein, the term "vehicle operation mode" refers to the operating mode of the vehicle. The electric vehicle operation mode may include one of an autonomous driving mode, an autonomous mode, a non-autonomous mode, and a semi-autonomous mode.

[0126] As used herein, the term "vehicle fuel operation mode" refers to the fuel mode in which the vehicle operates. The vehicle fuel operation mode includes one of a hybrid mode, an electric mode, and a combustion fuel mode.

[0127] As used herein, the term "mutation" refers to an unexpected change. A mutation may also refer to an irregular change in an indicator or value.

[0128] As used herein, the term "event" refers to something that happens. An event may be an organized and planned event. An event may also be an unorganized and unplanned event. An event may be due to weather conditions. An event may be due to surrounding vehicles (e.g., traffic conditions, etc.). An event may be the result of activities occurring outside the vehicle. An event may be the result of activities occurring inside the vehicle.

[0129] As used herein, the term "robotic arm" refers to a machine integrated with a charging station for inserting a charger into a charging port and / or removing it from the charging port. The robotic arm can also be a machine not integrated with the charging station. The robotic arm can be a collapsible arm-like structure.

[0130] As used herein, the term "reserved charging position" refers to a charging position reserved for a vehicle in a charging station. The charging station may include one or more charging positions. A charging position refers to a space where a vehicle parks and receives charging from a charging device.

[0131] As used herein, the term "reserved charging unit" refers to a charging unit reserved for charging a vehicle in a charging station. The charging station may include one or more charging units. A charging unit refers to a device or system that supplies power to a vehicle through a charging port. The charging unit can charge the vehicle by wired or wireless means.

[0132] As used herein, the term "insert" refers to inserting a charging cable into a charging port. The charging cable may include a charger plug that exactly matches the charging port. The charger plug may include metal pins capable of supplying power to the vehicle to charge the battery pack.

[0133] As used herein, the term "remove" refers to removing the charging cable from the charging port.

[0134] As used herein, the term "predefined amount of electricity" refers to a predefined amount of electricity supplied to a vehicle for charging the vehicle.

[0135] As used herein, the term "predetermined charging duration" refers to a predetermined time for supplying a predefined amount of electricity to a vehicle to charge the vehicle.

[0136] As used herein, the term "area" refers to one or more areas surrounding or encircling the direction of a vehicle. The area includes one or more charging stations. The area includes a predefined area. The one or more areas can be continuous. The one or more areas can be discontinuous.

[0137] As used herein, the term "real-time position" refers to the current position of any object (e.g., a vehicle) at this point in time. The real-time position refers to the real-time position of the vehicle.

[0138] As used herein, the term "itinerary" refers to a user's travel plan. The itinerary includes scheduled / planned events, their locations, durations, times, dates, etc. In one embodiment, the "itinerary" refers to an itinerary to go to work, an itinerary to see a doctor, an itinerary to go to the grocery store, etc. The itinerary can also include other less common itineraries, such as vacation itineraries, long-distance trips, short-term trips, express trips, etc. The itinerary can be divided into an estimated departure time, a departure point, a start time, a destination, and an end time. The itinerary can also include intermediate waypoints that further define the route. The itinerary can include, but is not limited to, a departure point, a departure time, a destination, an expected route, and optional intermediate waypoints.

[0139] As used herein, the term "occupancy status" refers to information regarding whether a charging station or a corresponding or reserved charging unit is occupied. The occupancy status can be one of "available" and "occupied". When another vehicle blocks or obstructs the charging station or the reserved charging unit, the occupancy status is indicated as "occupied". When there is no charging session for a vehicle reserved at the charging station, the occupancy status can also be indicated as "occupied". When no other vehicle blocks or obstructs the charging station, the occupancy status is indicated as "available". When there is a reserved charging session waiting for a reserved vehicle at the reserved charging unit, the occupancy status can also be indicated as "available".

[0140] As used herein, the term "operational status" refers to information regarding whether a charging station is charging a vehicle or whether the charging station is available for charging a vehicle. The operational status can be one of "available" and "occupied". When the charging station is charging a vehicle, the operational status is indicated as "occupied". When there is no charging session reserved for a vehicle at the charging station, the operational status can also be indicated as "occupied". When the charging station is ready to charge a vehicle, the operational status is indicated as "available". When there is a charging session reserved for a vehicle at the charging station, the operational status can also be indicated as "available".

[0141] As used herein, the term "occupant" refers to a person sitting in a vehicle. The occupant can be a child, a kid, an adult, and an elderly person. The occupant can be a driver, a passenger, etc. The occupant can leave the vehicle. If the occupant leaves the vehicle, the vehicle can operate in an autonomous driving mode.

[0142] As used herein, the term "reserved charging session" refers to an event arranged to charge a vehicle using a corresponding charging unit in a charging station.

[0143] As used herein, the term "content" refers to objects, data, visual representations, information, etc. The content may contain meaningful information. The content may also contain meaningless random information.

[0144] As used herein, the term "vehicle identification" refers to an identification code of a specific vehicle. The vehicle identification (VIN) is a unique code used to identify an individual motor vehicle, including a serial number.

[0145] As used herein, the term "vehicle type" refers to the classification type of a vehicle. The vehicle type includes one of an autonomous vehicle, a non-autonomous vehicle, and a semi-autonomous vehicle.

[0146] As used herein, the term "predetermined time period" refers to the time period for predetermining the execution of an event. For example, the term "predetermined time period" refers to the time, start time, and end time for predetermining the execution of an event of charging.

[0147] The term "coordinates" as used herein refers to a set of values that indicate an exact position.

[0148] As used herein, the term "predetermined proximity" refers to a predefined distance between two objects (e.g., a vehicle and a charging station).

[0149] The term "status query" as used herein refers to a message for querying at least one of the operating status and the occupancy status of a charging station. A vehicle can receive the operating status and the occupancy status from the charging station via a message or any other format in response to the status query message.

[0150] The term "first route" as used herein refers to a route that guides / leads a vehicle to a reserved charging station.

[0151] The term "second route" as used herein refers to a route that guides / leads a vehicle to a subsequent charging station.

[0152] The term "reserved charging station" as used herein refers to a charging station reserved for charging a vehicle.

[0153] The term "subsequent charging station" as used herein refers to a charging station after the reserved charging station. The subsequent charging station is the next nearest charging station. When at least one of the first operating status and the first occupancy status is occupied, the subsequent charging station can be queried and / or reserved.

[0154] 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 encryption primitives. The protocol describes the use of algorithms. A protocol detailed enough includes detailed information about data structures and representations to implement multiple interoperable versions of a program. Encryption protocols are widely used for secure application-level data transmission. An encryption protocol generally 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.

[0155] Secure application layer data transfer widely uses cryptographic protocols. A cryptographic protocol typically includes 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.

[0156] 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.

[0157] In this document, "unauthorized access" means that someone uses another person's account or other methods to access a website, program, server, service, or other system. For example, if someone has been guessing the password or username of another person's account before obtaining access, it is considered unauthorized access.

[0158] The term "IoT" as used in this article represents the Internet of Things, which describes a network of physical objects, "things", or objects embedded with sensors, software, and other technologies, for the purpose of connecting and exchanging data with other devices and systems over the Internet.

[0159] "Machine learning" as used in this article refers to algorithms that enable a computer to learn without explicit programming, 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 as "neural networks" in this article), deep learning neural networks, logistic regression, discriminant analysis, random forests, linear regression, rule-based machine learning, naive Bayes, nearest neighbors, decision trees, decision tree learning, and hidden Markov, etc. For clarity, algorithms such as linear regression or logistic regression can also be used as part of the machine learning process. However, it should be understood that using linear regression or another algorithm as part of the machine learning process is different from performing statistical analysis (such as regression) using a spreadsheet program. The machine learning process can continuously learn and adjust the classifier as new data emerges 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.

[0160] The term "dashboard" as used here 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.

[0161] The "database" as used here refers to an organized collection of information for easy access, management, and update. Computer databases typically contain a collection of data records or files.

[0162] As used herein, the term "data set" (or "data sets") 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.

[0163] 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 a variety of 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, the sensor can be removably or fixedly mounted within a vehicle and can be arranged in various configurations to provide information to an autonomous operation function. The 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 an occupant (such as a child, adult, kid, passenger, driver, etc.) to determine the occupant weight and the vehicle weight.

[0164] The term "vehicle" as used herein refers to a vehicle used for transporting people or goods. Examples of vehicles include cars, sedans, trucks, buses, etc.

[0165] The term "electronic control unit" (ECU), also known as "electronic control module" (ECM), is generally a module that controls one or more subsystems. Herein, the ECU can be installed in an automobile 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 an embedded system in automotive electronics. In another example, the electronic control unit is wirelessly coupled to automotive electronics.

[0166] 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, the instructions 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.

[0167] The term "vehicle data bus" as used herein 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.

[0168] 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 impostor). This may also include an operator using passwords and codes. The handshake signals are transmitted back and forth over the communication network to establish a valid connection between 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.

[0169] As used herein, the term "infotainment system" or "in-vehicle infotainment system" (IVI) refers to a combination of vehicle systems for providing entertainment and information. In one example, information can be delivered to the driver and passengers / occupants of the vehicle via 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, operating systems, controller area network (CAN), low-voltage differential signaling (LVDS), and other network protocol support (as required), connection modules, automotive sensor integration, digital instrument clusters, etc.

[0170] As used herein, the term "autonomous mode" refers to a mode of vehicle operation that is independent and unsupervised.

[0171] As used herein, the term "autonomous communication" includes communication over a period of time with minimal supervision in different scenarios and is not 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 for autonomous communication.

[0172] 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.

[0173] An "alert" or "alert signal" refers to communication that draws 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.

[0174] 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 a description of what is actually happening in the video (so-called metadata), 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, poses, gestures, etc.), as well as their appearance and actions.

[0175] The term "cybersecurity" as used in this article refers to the application of technologies, processes, and controls to protect systems, networks, programs, devices, and data from cyberattacks.

[0176] The term "cybersecurity module" as used in this article refers to a module of an application that contains 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 the unauthorized use of systems, networks, and technologies. It includes, but is not limited to, critical infrastructure security, application security, network security, cloud security, and Internet of Things (IoT) security.

[0177] The term "encryption" as used in this article 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 a code, especially to prevent unauthorized access. It may also refer to hiding information or data by converting it into a 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.

[0178] The term "decryption" as used in this article refers to the process of converting encrypted information back to its original format. It is usually 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 password. This term can be used to describe the method of decrypting data manually or using the correct code or key to decrypt the data.

[0179] The term "cybersecurity threat" as used in this article refers to any possible malicious attack aimed at illegally accessing data, disrupting digital operations, or destroying information. Malicious acts include, but are not limited to, destroying data, stealing data, or disrupting general digital life. Cyber 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.

[0180] The term "hash value" as used in this article 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, namely 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).

[0181] 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 find 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 verify whether the data in a database is accurate and whether it operates as expected in a given application.

[0182] As used herein, the term "alarm" refers to an event triggered when a component or system in a system fails or does not operate as expected. When an event occurs, the system may enter an alarm state. An alarm indication signal is a visual signal indicating the alarm state. For example, when a cybersecurity threat is detected, a system administrator may receive an alarm via a sound alarm, message, glowing LED, pop-up window, etc. The alarm indication signal may be reported downstream from the detection device to prevent adverse situations or chain effects.

[0183] As used herein, the term "network" may include the Internet, local area network, wide area network, or a combination thereof. A network may include one or more networks or communication systems, such as the Internet, telephone system, satellite network, cable television network, and various other private and public networks. Additionally, a connection may include a wired connection (e.g., wire, cable, fiber optic line, etc.), wireless connection, or a combination thereof. Furthermore, although not shown, other computers, systems, devices, and networks may also be connected to the network. A network refers to any group 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 those servers.

[0184] The term "autonomous vehicle", also known as a self-driving vehicle, driverless vehicle, robotic vehicle, refers to a vehicle that employs vehicle automation, i.e., a ground vehicle capable of sensing its surrounding environment and safely driving with little or no human intervention. An autonomous vehicle combines various sensors to sense its 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), odometer, and inertial measurement unit. A control system designed for this purpose interprets the sensor information to determine an appropriate navigation path as well as obstacles and relevant signs.

[0185] 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 in a lane or park itself, but cannot drive autonomously. A semi-autonomous vehicle can drive independently to some extent.

[0186] As used herein, the term "connection" refers to a communication link. It refers to 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 on a multiplexed medium (such as a radio 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, usually 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.

[0187] As used herein, the term "protocol" refers to the procedures 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 in 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.

[0188] As used herein, the term "component" is broadly interpreted as hardware, firmware, and / or a combination of hardware, firmware, and software.

[0189] 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.

[0190] The computer-readable program instructions described herein can be downloaded from a computer-readable storage medium to a corresponding computing / processing device, and / or downloaded to an external computer or 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 can 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 corresponding computing / processing device. The computer-readable program instructions for performing the operations of one or more embodiments described herein can 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 can 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 can be connected to the computer through any type of network connection, including a local area network (LAN) and / or a wide area network (WAN), and / or can be connected to an external computer (e.g., using an Internet service provider via the Internet). 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 to execute the computer-readable program instructions in order to perform aspects of one or more embodiments described herein.

[0191] 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 flowcharts and / or block diagrams, and combinations of blocks in the flowcharts 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 can create a 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 operate 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.

[0192] 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 diagram 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 block 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 flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, 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.

[0193] Although 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. In addition, 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 through a communication network perform tasks, may also practice the aspects shown. However, an independent computer may practice one or more aspects (if not all) 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.

[0194] As used in this application, the terms "component", "system", "platform", "interface", etc. may refer to and / or include a computer-related entity or an entity related to an operating machine with one or more specific functions. The entities described herein may be hardware, a combination of hardware and software, software, or software in execution. For example, a component may 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. By way of example, both an application running on a server and the server can be components. One or more components may reside in a process and / or an execution thread, and a component may be located on one computer and / or distributed between two or more computers. In another example, various components may execute from various computer-readable media having various data structures stored thereon. Components may communicate through 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 with other systems through a network such as the Internet) via a signal. As another example, a component may be a device having a particular function provided by a mechanical component operated by an electrical or electronic circuit, which is operated by a software and / or firmware application executed by a processor. In such a case, the processor may be internal and / or external to the device and may execute at least a portion of the software and / or firmware application. As another example, a component may be a device having a particular function provided by an electronic component without a mechanical component, where the electronic component may include a processor and / or other means to execute software and / or firmware, which at least partially imparts the function of the electronic component. In one aspect, a component may simulate an electronic component through a virtual machine (e.g., within a cloud computing system).

[0195] In this specification, the term "processor" may 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 may 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 may 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 may implement a processor.

[0196] 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 herein may be volatile memory or non-volatile memory, or may include both volatile memory and non-volatile memory. By way of example, and not limitation, non-volatile memory may 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 may include RAM, which may be used, for example, as an external cache memory. By way of example, and not limitation, RAM may 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). Additionally, the memory components of the systems and / or computer-implemented methods described herein include but are not limited to these and / or any other suitable types of memory.

[0197] 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, where the terms "including", "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 "comprising", as "comprising" is interpreted to be inclusive when used as a transitional word in the claims.

[0198] 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 those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The terms used herein best explain the principles of the embodiments, practical applications, and / or technical improvements over the technologies found in the market, and / or enable other ordinary skilled persons in the art to understand the embodiments described herein.

[0199] Technical problem 1: The current charging system is not the best option for charging and there is no efficient reservation system. For example, when a driver wants to charge a vehicle, the driver does not know whether there is a charger available for charging, whether it is for short-term charging or long-term charging. In the case where the state of charge is below the threshold and there is no available charger, the driver will be in a difficult situation. Therefore, an automatic reservation system is needed to ensure that when the state of charge is below the threshold, the system will automatically find an available charger and reserve the charger.

[0200] Technical Solution 1: In one aspect, the system detects that the charge level of the vehicle has dropped below a threshold. The system a) alerts the driver; b) determines a geographical range based on available charge, weather conditions, total weight, driver driving habits, etc.; c) scans the area within the geographical range for available charging stations; d) establishes communication with the nearest charging station to identify available chargers (the identification algorithm includes determining the time to reach the available charging station and whether the charger is available within the duration required for the vehicle to charge above the threshold or above the level required based on the final destination or other factors); e) transmits parameters (e.g., ETA, payment information, vehicle identification, etc.) to reserve the charging station. In one aspect, the system displays the best route to the reserved location and optimizes the available power. The driver can initiate autonomous driving to allow the system to drive to the reserved charging station. (For more details on the operation). In one aspect, the system can initiate wireless charging or automatically connect to the reserved charging station. In one aspect, the vehicle includes a charging port or device that can automatically connect to the charging station without driver assistance. In another aspect, the vehicle is equipped with a communication module to communicate with a charging station robot that can connect the vehicle to the charging station without a special port.

[0201] In one aspect, a system is described. Figure 1A block diagram of a system according to one or more embodiments is shown. The system includes: a sensor module 102; and a control module 104. The control module 104 includes a processor 106; and a memory 108 communicatively coupled to the processor 106. The memory 108 includes a sensor control module that, when executed by the processor 106, causes the processor to: determine a first state of charge of one or more batteries associated with a vehicle (step 103); determine whether the first state of charge is below a threshold state of charge level (step 105); determine one or more first geographical ranges including one or more first charging stations based on the first state of charge (step 107); determine one or more charge consumption factors affecting charge consumption in the one or more batteries (step 109); estimate charge consumption en route based on the one or more charge consumption factors (step 111); determine a second state of charge based on the charge consumption (step 113); determine one or more second geographical ranges including one or more second charging stations based on the second state of charge (step 115); and schedule one or more charging sessions with the one or more second charging stations to charge the one or more batteries (step 117). In one embodiment, the processor 106 is operable to preset the threshold state of charge level. In one embodiment, the sensor module includes at least one of the following: one or more weight sensors, one or more load cells, 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 voltmeters, one or more temperature sensors, one or more light sensors, one or more capacitive load cells, and one or more accelerometers.

[0202] The first state of charge includes a measurement of the first amount of electrical charge available in the one or more batteries at a particular point in time. The first state of charge of the one or more batteries can be expressed as a percentage. A processor determines the first state of charge (SoC) of the one or more batteries by performing the following technical steps using one or more voltage sensors. The sensor module can include the one or more voltage sensors. The one or more voltage sensors can also be located on a battery management system attached to or embedded in the battery pack. The battery pack can include one or more batteries. The one or more batteries can be the same or different batteries. The processor is in electrical communication with the one or more voltage sensors. The one or more voltage sensors are configured to continuously or periodically detect the voltage of the battery pack. The processor receives the detected battery pack voltage from the one or more voltage sensors. Then, the processor determines the average voltage of the battery pack by averaging the detected battery pack voltage over a predetermined period of time. Then, the processor determines the current operating state of the battery pack based on the detected battery pack voltage. Then, the processor determines the first state of charge of the battery pack (i.e., the one or more batteries) based on the current operating state of the battery pack and the average voltage of the battery pack. In one embodiment, the second state of charge (SoC) of the battery pack can also be determined in a similar manner as described above based on a later operating state of the battery pack. Other sensors (e.g., hydrometers, voltmeters, etc.) can also be used to determine the state of charge of the battery.

[0203] Then, the processor is configured to determine whether the first state of charge (SoC) of the one or more batteries is below a threshold state of charge level. The processor is in electrical communication with one or more voltmeters. The one or more voltmeters serve as SoC indicators. The one or more voltmeters indicate when the first state of charge (SoC) of the one or more batteries is below the threshold state of charge level and communicate it to the processor. The processor determines that the first state of charge (SoC) of the one or more batteries is below the threshold state of charge level based on the communication received from the one or more voltmeters.

[0204] The processor determines one or more first geographical ranges including one or more first charging stations based on the first state of charge. The one or more first geographical ranges include one or more first charging stations. The processor performs the following technical steps for determining the one or more first geographical ranges. The processor uses an artificial intelligence engine to determine the distance range that the vehicle can travel using the first state of charge. Then, the processor uses the artificial intelligence engine to identify one or more first areas around the vehicle, the one or more first areas including the one or more first charging stations available for charging. Then, the processor uses the artificial intelligence engine to determine one or more first geographical ranges that cover the one or more first areas. Then, the processor uses the artificial intelligence engine to provide the layout of the one or more first geographical ranges.

[0205] In one embodiment, the processor identifies one or more first regions near the vehicle by performing the following technical steps. The processor determines the real-time position of the vehicle. Then, the processor determines one or more first charging stations around the real-time position of the vehicle. Then, the processor maps the one or more first charging stations around the real-time position of the vehicle into one or more first regions. Then, the processor marks the one or more first charging stations within the one or more first regions.

[0206] The processor determines one or more charge consumption factors that affect the charge consumption in the one or more batteries. In one embodiment, the one or more charge consumption factors include one or more external charge consumption factors. In another embodiment, the one or more charge consumption factors include one or more internal charge consumption factors. The processor determines the one or more charge consumption factors that affect the charge consumption in the one or more batteries by performing the following technical steps. The processor continuously senses one or more external charge consumption factors around the vehicle using a sensor module. Then, the processor determines at least one of a sudden change and an abnormal increase in the charge consumption of the vehicle. Then, the processor associates at least one of the sudden change and the abnormal increase in the charge consumption with the one or more external charge consumption factors. The processor also uses an artificial intelligence engine to learn the one or more external charge consumption factors and the charge consumption based on this association.

[0207] In one embodiment, the one or more external charge consumption factors include at least one of environmental conditions, road surface conditions, the distance between the one or more first charging stations and the vehicle, traffic conditions, waiting time, and driving mode. Environmental conditions include information on at least one of weather, climate, temperature, wind, storm, tornado, snow, sleet, and rain. Road surface conditions include information on at least one of surface smoothness, surface friction, surface inclination, surface deviation, surface smoothness, and surface material. Traffic conditions include information on at least one of intersection area waiting time, traffic signal waiting time, travel time from the current position of the vehicle to the destination, one or more nearby vehicles, lanes, predefined driving speed, and obstacles. Driving mode includes information on at least one of the driver's driving profile, driving speed, and driving efficiency score.

[0208] In one embodiment, the processor determines one or more charge consumption factors that affect the charge consumption in one or more batteries by performing the following technical steps. The processor continuously senses one or more internal charge consumption factors using a sensor module. The processor determines at least one of a mutation and an abnormal increase in the charge consumption of the vehicle. The processor associates at least one of the mutation and the abnormal increase in the charge consumption with the one or more internal charge consumption factors. The processor uses an artificial intelligence engine to learn the one or more internal charge consumption factors and the charge consumption based on the association.

[0209] In one embodiment, the one or more internal charge consumption factors include at least one of vehicle weight, the health state of one or more batteries, occupant weight, luggage weight, vehicle specifications, vehicle operation mode, and vehicle fuel operation mode. The vehicle operation mode includes one of an autonomous driving mode, a non-autonomous mode, an autonomous mode, and a semi-autonomous mode. The vehicle fuel operation mode includes one of a hybrid mode, an electric mode, and a combustion fuel mode.

[0210] In one embodiment, the processor determines one or more charge consumption factors that affect the charge consumption in the one or more batteries by performing the following technical steps. The processor continuously senses at least one of one or more events, one or more activities, and one or more actions using a sensor module. The processor uses an artificial intelligence engine to determine one or more charge consumption factors that cause at least one of the one or more events, the one or more activities, and the one or more actions. Then, the processor determines the charge consumption of at least one of the one or more events, the one or more activities, and the one or more actions. The processor uses the artificial intelligence engine to learn them by associating the one or more charge consumption factors with the charge consumption. Then, the processor estimates the charge consumption for the one or more charge consumption factors that will occur in the future.

[0211] In one embodiment, the one or more events include the vehicle traveling a predefined distance on an inclined road surface. For example, the processor uses an artificial intelligence engine to determine the road surface inclination as one or more charge consumption factors that cause the one or more events. In another embodiment, the one or more events include the vehicle traveling with a predefined load. For example, the processor uses an artificial intelligence engine to determine the occupant weight as one or more charge consumption factors that cause the one or more events. In another embodiment, the one or more events include the vehicle traveling in a traffic environment. For example, the processor uses an artificial intelligence engine to determine the traffic conditions as one or more charge consumption factors that cause the one or more events. In another embodiment, the one or more events include a sudden discharge of one or more batteries. For example, the processor uses an artificial intelligence engine to determine the health status of the one or more batteries as one or more charge consumption factors that cause the one or more events.

[0212] Then, the processor determines a second state of charge based on the charge consumption. In one embodiment, the second state of charge includes an estimate of the second charge amount in the one or more batteries considering the one or more charge consumption factors. In one embodiment, the second state of charge (SoC) of the battery pack can be determined in a manner similar to the determination of the first state of charge described above. Other sensors (such as a hydrometer, a voltmeter, etc.) can also be used to determine the state of charge of the battery.

[0213] Then, the processor determines one or more second geographical ranges including one or more second charging stations based on the second state of charge. In one embodiment, the one or more second geographical ranges cover a part of the one or more first geographical ranges. The processor determines one or more second geographical ranges including one or more second charging stations based on the second state of charge. The processor determines the one or more second geographical ranges by performing the following technical steps. The processor uses an artificial intelligence engine to determine the distance range that the vehicle can travel using the second state of charge. The processor uses an artificial intelligence engine to identify one or more second areas around the vehicle, and the one or more second areas include one or more second charging stations available for charging. The processor uses an artificial intelligence engine to determine the one or more second geographical ranges covering the one or more second areas. The processor uses an artificial intelligence engine to provide the layout of the one or more second geographical ranges. In one embodiment, the one or more second geographical ranges are different from the one or more first geographical ranges. In another embodiment, the one or more second geographical ranges completely overlap with the one or more first geographical ranges.

[0214] In one embodiment, the processor uses an artificial intelligence engine to identify one or more second regions near the vehicle by performing the following technical steps. The processor determines the real-time position of the vehicle. The processor determines one or more second charging stations around the real-time position of the vehicle. The processor maps one or more second charging stations around the real-time position of the vehicle into one or more second regions. The processor marks one or more second charging stations within the one or more second regions.

[0215] In one embodiment, the processor is operable to establish communication between one or more second charging stations and the vehicle. The communication can be wireless communication. In one embodiment, the communication can be wired communication.

[0216] Then, the processor schedules one or more charging sessions with one or more second charging stations to charge the one or more batteries. In one embodiment, the processor schedules one or more second charging stations to charge the one or more batteries by performing the following technical steps. The processor determines the time when the vehicle arrives at the location of the one or more second charging stations. The processor determines the charging duration for the one or more batteries to complete charging. In one embodiment, the processor determines the charging duration for the one or more batteries to reach a predefined level of charge. In one embodiment, the processor determines the duration for the one or more batteries to reach a predefined level of charge to complete the journey. The processor determines the remaining time for the vehicle based on the journey associated with the vehicle user. The remaining time can be the time the user spends in a coffee shop. The remaining time can be the time the user is engrossed in work. Then, the processor uses the artificial intelligence engine to calculate one or more charging sessions based on at least one of the arrival time, charging duration, and remaining time. Then, the processor compiles one or more messages to be sent to the one or more second charging stations based on the one or more charging sessions. The one or more messages include information such as vehicle identification, vehicle location, distance between the vehicle and the charging station, charging sequence, charging date, second state of charge, start time of the charging session, end time of the charging session, predefined time period, and charging duration.

[0217] In one embodiment, the processor can enable the automatic mode of the vehicle based on one or more charging sessions. In another embodiment, the processor transmits instructions to the electric drive unit to automatically maneuver the vehicle to the one or more second charging stations before a predefined time period.

[0218] In one aspect, a method for scheduling a charging session is described. Figure 2A method for a reservation charging session according to one or more embodiments is shown. The method includes the execution of the following technical steps: determining a first state of charge of one or more batteries associated with a vehicle (step 203); determining whether the first state of charge is below a threshold state of charge level (step 205); determining one or more first geographical ranges including one or more first charging stations based on the first state of charge (step 207); determining one or more charge consumption factors affecting charge consumption in the one or more batteries (step 209); estimating charge consumption based on the one or more charge consumption factors (step 211); determining a second state of charge based on the charge consumption (step 213); determining one or more second geographical ranges including one or more second charging stations based on the second state of charge (step 215); and reserving one or more charging sessions with the one or more second charging stations to charge the one or more batteries (step 217).

[0219] In one embodiment, determining one or more first geographical ranges including one or more first charging stations based on the first state of charge includes: using an artificial intelligence engine to determine a distance range within which the vehicle can travel using the first state of charge; using an artificial intelligence engine to identify one or more first areas around the vehicle, the one or more first areas including the one or more first charging stations available for charging; using an artificial intelligence engine to determine the one or more first geographical ranges covering the one or more first areas; and using an artificial intelligence engine to provide a layout of the one or more first geographical ranges.

[0220] In one embodiment, using an artificial intelligence engine to identify one or more first areas near the vehicle, the one or more first areas including the one or more first charging stations available for charging, includes: determining a real-time position of the vehicle; determining one or more first charging stations around the real-time position of the vehicle; mapping the one or more first charging stations around the real-time position of the vehicle into the one or more first areas; and marking the one or more first charging stations within the one or more first areas.

[0221] In one embodiment, determining one or more charge consumption factors affecting charge consumption in the one or more batteries includes: using a sensor module to continuously sense one or more external charge consumption factors around the vehicle; determining at least one of a mutation and an abnormal increase in the charge consumption of the vehicle; correlating at least one of the mutation and the abnormal increase in the charge consumption with the one or more external charge consumption factors; and using an artificial intelligence engine to learn the one or more external charge consumption factors and the charge consumption based on the correlation.

[0222] In one embodiment, determining one or more charge consumption factors that affect charge consumption in one or more batteries includes: continuously sensing one or more internal charge consumption factors using a sensor module; determining at least one of a mutation and an abnormal increase in the charge consumption of the vehicle; associating at least one of the mutation and the abnormal increase in the charge consumption with one or more internal charge consumption factors; and using an artificial intelligence engine to learn one or more internal charge consumption factors and charge consumption based on the correlation.

[0223] In one embodiment, determining one or more charge consumption factors that affect charge consumption in the one or more batteries includes: continuously sensing at least one of one or more events, one or more activities, and one or more actions using a sensor module; using an artificial intelligence engine to determine one or more charge consumption factors that cause at least one of the one or more events, the one or more activities, and the one or more actions; determining the charge consumption of at least one of the one or more events, the one or more activities, and the one or more actions; and using an artificial intelligence engine to learn the one or more charge consumption factors and charge consumption.

[0224] In one embodiment, determining one or more second geographic ranges including one or more second charging stations based on a second state of charge includes: using an artificial intelligence engine to determine a distance range within which the vehicle can travel using the second state of charge; using an artificial intelligence engine to identify one or more second regions around the vehicle, the one or more second regions including one or more second charging stations available for charging; using an artificial intelligence engine to determine the one or more second geographic ranges that cover the one or more second regions; and using an artificial intelligence engine to provide a layout of the one or more second geographic ranges.

[0225] In one embodiment, using an artificial intelligence engine to identify one or more second regions near the vehicle, the one or more second regions including one or more second charging stations available for charging, includes: determining the real-time position of the vehicle; determining one or more second charging stations around the real-time position of the vehicle; mapping the one or more second charging stations around the real-time position of the vehicle into one or more second regions; and marking the one or more second charging stations within the one or more second regions.

[0226] In one embodiment, the method further includes: establishing communication between one or more second charging stations and the vehicle.

[0227] In one embodiment, reserving the one or more second charging stations to charge the one or more batteries includes: determining the time when the vehicle arrives at the location where the one or more second charging stations are located; determining the charging duration for the one or more batteries to complete charging; determining the remaining time for the vehicle based on a trip associated with a user of the vehicle; using an artificial intelligence engine to calculate one or more charging sessions based on at least one of the arrival time, the charging duration, and the remaining time; and compiling one or more messages to be sent to the one or more second charging stations based on the one or more charging sessions.

[0228] In another aspect, a non-transitory computer-readable storage medium is described. Figure 3 A non-transitory computer-readable storage medium according to one or more embodiments is shown. The non-transitory computer-readable storage medium includes a series of instructions that, when executed by a processor, cause the following steps: determining a first state of charge of one or more batteries associated with a vehicle (step 303); determining whether the first state of charge is below a threshold state-of-charge level (step 305); determining one or more first geographic ranges including one or more first charging stations based on the first state of charge (step 307); determining one or more charge consumption factors that affect charge consumption in the one or more batteries (step 309); estimating charge consumption based on the one or more charge consumption factors (step 311); determining a second state of charge based on the charge consumption (step 313); determining one or more second geographic ranges including one or more second charging stations according to the second state of charge (at step 315); and reserving one or more charging sessions with the one or more second charging stations to charge the one or more batteries (at step 317).

[0229] In one embodiment, determining one or more first geographic ranges including one or more first charging stations based on the first state of charge is caused by the following steps: using an artificial intelligence engine to determine a distance range that the vehicle can travel using the first state of charge; using an artificial intelligence engine to identify one or more first regions around the vehicle, the one or more first regions including the one or more first charging stations available for charging; using an artificial intelligence engine to determine the one or more first geographic ranges covering the one or more first regions; and using an artificial intelligence engine to provide a layout of the one or more first geographic ranges.

[0230] In one embodiment, an artificial intelligence engine is used to identify one or more first regions near the vehicle, and the one or more first regions include the one or more first charging stations available for charging, which is caused by the following steps: determining the real-time position of the vehicle; determining one or more first charging stations around the real-time position of the vehicle; mapping the one or more first charging stations around the real-time position of the vehicle into the one or more first regions; and marking the one or more first charging stations within the one or more first regions.

[0231] In one embodiment, determining one or more charge consumption factors that affect the charge consumption in one or more batteries is caused by the following steps: continuously sensing one or more external charge consumption factors around the vehicle using a sensor module; determining at least one of a mutation and an abnormal increase in the charge consumption of the vehicle; associating at least one of the mutation and the abnormal increase in the charge consumption with the one or more external charge consumption factors; and using an artificial intelligence engine to learn the one or more external charge consumption factors and the charge consumption based on this association.

[0232] In one embodiment, determining one or more charge consumption factors that affect the charge consumption in one or more batteries is caused by the following steps: continuously sensing one or more internal charge consumption factors using a sensor module; determining at least one of a mutation and an abnormal increase in the charge consumption of the vehicle; associating at least one of the mutation and the abnormal increase in the charge consumption with the one or more internal charge consumption factors; and using an artificial intelligence engine to learn the one or more internal charge consumption factors and the charge consumption based on this association.

[0233] In one embodiment, determining one or more charge consumption factors that affect the charge consumption in one or more batteries is caused by the following steps: continuously sensing at least one of one or more events, one or more activities, and one or more actions using a sensor module; using an artificial intelligence engine to determine one or more charge consumption factors that cause at least one of the one or more events, the one or more activities, and the one or more actions; determining the charge consumption of at least one of the one or more events, the one or more activities, and the one or more actions; and using an artificial intelligence engine to learn the one or more charge consumption factors and the charge consumption.

[0234] In one embodiment, determining one or more second geographic ranges that include one or more second charging stations based on a second state of charge includes: using an artificial intelligence engine to determine a distance range that a vehicle can travel using the second state of charge; using an artificial intelligence engine to identify one or more second regions around the vehicle, the one or more second regions including one or more second charging stations available for charging; using an artificial intelligence engine to determine the one or more second geographic ranges that encompass the one or more second regions; and using an artificial intelligence engine to provide a layout of the one or more second geographic ranges.

[0235] In one embodiment, using an artificial intelligence engine to identify one or more second regions near a vehicle, the one or more second regions including one or more second charging stations available for charging, causes a processor to: determine a real-time location of the vehicle; determine one or more second charging stations around the real-time location of the vehicle; map the one or more second charging stations around the real-time location of the vehicle into the one or more second regions; and mark the one or more second charging stations within the one or more second regions.

[0236] In one embodiment, the non-transitory computer-readable storage medium further causes: establishing communication between one or more second charging stations and the vehicle.

[0237] In one embodiment, reserving one or more second charging stations to charge one or more batteries includes: determining a time when the vehicle arrives at a location where the one or more second charging stations are located; determining a charging duration for the one or more batteries to complete charging; determining a remaining time of the vehicle based on a trip associated with a user of the vehicle; using an artificial intelligence engine to calculate one or more charging sessions based on at least one of the arrival time, the charging duration, and the remaining time; and compiling one or more messages to be sent to the one or more second charging stations based on the one or more charging sessions.

[0238] As an example, Figure 4 A block diagram for charging a vehicle according to one or more embodiments is shown. Figure 4The figures shown include an energy source 402, a charging station 404, a vehicle 406, and an external device 408. The energy source 402 supplies power to the charging station 404. The energy source 402 can be a solar power station. The energy source 402 can also be an electrical storage unit that obtains power from an external source. The energy source 402 can be a renewable energy source or a non-renewable energy source. The energy source 402 can also be a power grid. The charging station 404 is configured to charge the vehicle 406. The vehicle 406 can be an electric vehicle. The vehicle 406 can also be one of an autonomous vehicle and a non-autonomous vehicle. Note that the control module is a component within the vehicle 406 that is configured to locate and reserve a charging station. Communication is used to transmit information or instructions that are typically pre-arranged by the relevant parties. The signal can also be an electrical pulse or a radio wave. In one embodiment, the control module transmits a signal to the charging station to provide power to charge the vehicle. The external device 408 can be a smart device associated with a user that is configured to provide information to the user when the user is away from the vehicle and / or the charging station.

[0239] The vehicle 406 described herein can operate in an autonomous mode or a non-autonomous (self-driving) mode. The vehicle 406 includes a charging system, a battery pack, and a vehicle computer system. In one embodiment, the battery pack includes a single battery, and the single battery includes a plurality of battery cells. In another embodiment, the battery pack includes at least one of a first battery (e.g., a primary battery), a second battery (e.g., a secondary battery), and a third battery (e.g., a tertiary battery). The battery pack can include a plurality of identical batteries. The battery pack can include a plurality of non-identical batteries. In one embodiment, each battery of the battery pack can include the same capacity to store and deliver power. In another embodiment, each battery of the battery pack includes a different capacity to store and deliver power. Each battery of the battery pack can include a plurality of battery cells. Each battery of the battery pack can be electrically connected to each other for charging. The charging station 404 charges each battery of the battery pack. In one embodiment, the charging station 404 charges each battery of the battery pack in a random manner (e.g., a cyclic manner). In another embodiment, the charging station 404 charges each battery of the battery pack in sequence (e.g., in series). In yet another embodiment, the charging station 404 charges each battery of the battery pack simultaneously in parallel.

[0240] The vehicle computer system includes an infotainment system and / or an automotive head unit. The vehicle computer system includes an electronic control unit (ECU). The vehicle computer system may also include an in-vehicle gateway system. The in-vehicle gateway system is a device that connects two systems using different protocols. It is a system responsible for handling any outbound or inbound communication between any two vehicle ecosystem units. The vehicle computer system includes a user interface (e.g., a graphical user interface) that enables a user to interact with the system. In one embodiment, icons on the graphical user interface (GUI) or display of the infotainment system of the computer system are rearranged based on a priority score of the message content.

[0241] In one embodiment, the vehicle computer system enables a user to interact with the system via voice input. In another embodiment, the vehicle computer system enables a user to interact with and control the system via text input. The vehicle computer system including the infotainment system is a component that provides a unified hardware interface for the system, which includes a touch screen, a display screen, buttons, and system controls for numerous integrated information and entertainment functions. The vehicle computer system is configured to initiate and establish communication with a charging station 404. In one embodiment, the charging station 404 is also configured to initiate and establish communication with the vehicle computer system.

[0242] When the vehicle 406 is connected (e.g., via a wired connection, a wireless connection) to the charging station 404, a connection is established between the charging station 404 and the vehicle 406. The established connection can provide two-way communication. The charging station 404 and the vehicle 406 can send and receive signals and / or data bidirectionally. In another embodiment, the communication established between the charging station 404 and the vehicle 406 is via wired communication. In yet another embodiment, the communication established between the charging station 404 and the vehicle 406 is via wireless communication technology (e.g., Wi-Fi cellular technology, etc.).

[0243] As an example, Figure 5 a battery pack 502 including a single battery is shown 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 part X, a second part Y, and a third part Z. The first part X may include a first plurality of the plurality of battery cells of the battery. The second part Y may include a second plurality of the plurality of battery cells of the battery. The third part Z may include a third plurality of the plurality of battery cells of the battery.

[0244] The first part X, the second part Y, and the third part Z can be classified based on the health status information of their respective parts. The first part X can include a first health status. The second part Y can include a second health status. The third part Z can include a third health status. In one embodiment, the first part can refer to a part of a battery that has degraded battery cells. The second part can refer to a part of the battery that has healthy cells. The third part can refer to a part of the battery that has moderately degraded battery cells. The processor can be configured to detect the state of charge of a battery pack having at least one of healthy battery cells, degraded battery cells, and moderately degraded battery cells.

[0245] As an example, Figure 6 A battery pack including a plurality of batteries is shown 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 can include a plurality of first battery cells 604a. The second battery 602b can include a plurality of second battery cells 604b. The third battery 602c can include a plurality of third battery cells 604c. Each battery of the battery pack is electrically connected to be charged. The charging station charges each battery of the battery pack. The charging station can charge each battery of the battery pack in at least one of a random, series, and parallel manner.

[0246] The charging station can charge at least one of the first part X, the second part X, and the third part Z of the battery pack. The first part X of the battery pack refers to the degraded batteries (X = X1 + X2 + X3) in one or more batteries of the battery pack. The second part Y of the battery pack refers to the healthy batteries (Y = Y1 + Y2 + Y3) in one or more batteries of the battery pack. The third part Z of the battery pack refers to the moderately degraded batteries (Z = Z1 + Z2 + Z3) in one or more batteries of the battery pack. The healthy batteries 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.

[0247] The charging station is configured to map the battery pack based on the health status information. In one embodiment, the charging station maps at least one of the degraded batteries, healthy batteries, and moderately degraded batteries of the battery pack. After performing the battery pack mapping, the charging station calculates the state of charge considering the health status information.

[0248] For example, Figure 7Schematically shown is a battery pack including a battery 702 and a battery management system 706 according to one or more embodiments. The battery 702 in turn includes a plurality of battery cells 704. The battery management system 706 may include a microprocessor, a microcontroller, a programmable digital signal processor, or another programmable device. The battery management system 706 may also or alternatively include an application specific integrated circuit, a programmable gate array or 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 aforementioned microprocessor, microcontroller, or programmable digital signal processor), the processor may also include computer-executable code for controlling the operation of the programmable device. In one embodiment, the battery management system 706 is located within an electric vehicle. The battery management system 706 determines the state of charge (SoC) of the battery pack and communicates with a charging station via a vehicle computer system.

[0249] For example, Figure 8a Shown are one or more first geographic ranges 802 according to one or more embodiments. The one or more first geographic ranges 802 include one or more first charging stations 806A-N. The one or more first geographic ranges 802 may include one or more continuous or discontinuous first regions 804. The one or more first geographic ranges 802 may be determined based on a first state of charge. The processor estimates the range of distances that the vehicle can travel using the first state of charge. The processor then calculates the one or more first geographic ranges 802 based on the estimated range of distances.

[0250] As an example, Figure 8b Shown are one or more second geographic ranges 808 according to one or more embodiments. The one or more second geographic ranges 808 include one or more second charging stations 812A-N. The one or more second geographic ranges 808 may include one or more continuous or discontinuous second regions 810. The one or more second geographic ranges 808 may be determined based on a second state of charge. The second state of charge is the state of charge of the vehicle after charge consumption. The processor estimates the range of distances that the vehicle can travel using the second state of charge. The charge consumption may be attributed to one or more charge consumption factors. The processor then calculates one or more second geographic ranges 808 based on the estimated range of distances. The one or more second geographic ranges 808 may be different from the one or more first geographic ranges 802. The one or more second geographic ranges 808 may overlap with the one or more first geographic ranges 802. The one or more second geographic ranges 808 may cover a portion of the one or more first geographic ranges 802.

[0251] For example, Figure 9aShows the complete overlap of a first geographic range 902 and a second geographic range 908 according to one or more embodiments. The first geographic range 902 is determined based on a first state of charge, while the second geographic range 908 is determined based on a second state of charge. Since the second state of charge is determined based on charge consumption, the second state of charge may be equal to or less than the first state of charge. Therefore, it is obvious that the area of the second geographic range 908 may be equal to or less than the area of the first geographic range 902. For example, when the charge consumption is high, the second geographic range 908 may completely overlap with the first geographic range 902 (i.e., the entire area of the second geographic range 908 is within the area of the first geographic range 902).

[0252] For example, Figure 9b Shows a second geographic range 908 that covers a part of the first geographic range 902 according to one or more embodiments. The first geographic range 902 is determined based on a first state of charge, while the second geographic range 908 is determined based on a second state of charge. The first state of charge is the state of charge of the vehicle at a first specific time point. The second state of charge is the state of charge of the vehicle at a second specific time point (i.e., the charge consumption from the first state of charge point to the second state of charge point). Since the second state of charge is determined based on charge consumption, the second state of charge may be equal to or less than the first state of charge. Therefore, it is obvious that the area of the second geographic range 908 can be equal to or less than the area of the first geographic range 902. The second geographic range 908 may cover a part of the first geographic range 902. For example, when the charge consumption due to charge consumption factors is moderate, the second geographic range 908 may extend beyond the first geographic range 902 to cover a small part of the first geographic range 902.

[0253] As an example, Figure 9c Shows a second geographic range 908 and a first geographic range 902 that are different from each other according to one or more embodiments. For example, when the charge consumption due to charge consumption factors is low, the second geographic range 908 may completely extend beyond the first geographic range 902 such that the first geographic range 902 is different from the second geographic range 908.

[0254] As an example, Figure 10FIG. shows a schematic diagram of a charging station 404 according to one or more embodiments. In this embodiment, the charging station 404 includes at least two or more connector interfaces to allow power delivery to an electric vehicle having any one or more matching plug types. The charging station 404 includes a first connector 1002, a second connector 1004, a third connector 1006, and a fourth connector 1008. The connector positions shown in the figure are for illustration only and do not solidify the design specifications, that is, the plug type and side position can be changed as needed. The charging station 404 is capable of providing DC-to-DC fast charging and AC-to-DC charging. The charging station 404 can charge at least two electric vehicles simultaneously.

[0255] The charging station 404 includes a touch screen device 1010, which allows consumers / users to receive, send, and interact with media and content transmitted over the network. The touch screen device 1010 includes a touch screen of 15 inches (diagonal) or larger. The interface is interconnected with the charging station 404 using a web portal, a small business portal, a mobile application service, etc. The charging station 404 also includes buttons 1012, which allow consumers / users to select items displayed on the touch screen device 1010. The buttons 1012 are activators that cause the selected web content to be sent to a mobile application on the consumer / user's external device (e.g., phone). The buttons 1012 can be physically pressable buttons or screen-displayed buttons.

[0256] As an example, Figure 11 FIG. shows a message transmitted to the Figure 1 charging station described in. The message includes information on vehicle identification, vehicle position coordinates, distance between the vehicle and the charging station, charging sequence, charging date, second state of charge, charging session start time, charging session end time, predetermined time period, and charging duration.

[0257] The vehicle ID can be a serial identification number or a tag associated with the electric vehicle for identifying, recognizing, and locating the vehicle. The coordinates of the vehicle position represent the current position of the vehicle. The distance between the vehicle and the charging station refers to the distance between the vehicle and the charging station expressed in any unit (e.g., meters). The charging sequence represents the charging mode defined by the charging system or charging station based on battery parameters (e.g., state of charge, state of health) and charging time. The charging date represents the date of a predetermined charging session. The second state of charge refers to the state of charge of the vehicle after an estimated charge consumption. The charging session start time represents the time when the charging session is about to start. The charging session end time represents the time when the charging session is about to end / complete. The predetermined time period represents the range from the start time to the end time of the charging session. The charging duration represents the total time of a predetermined charging session.

[0258] Technical Problem 2: The current charging system is not the best option for charging, and there is no efficient reservation system. For example, when a driver wants to charge the vehicle, the driver doesn't know if there is a charger available for charging, whether it is for short-term or long-term charging. If the state of charge is below the threshold, there may be no available chargers, which may put the driver in a difficult situation. Therefore, an automatic reservation system is needed to ensure that when the state of charge is below the threshold, the system will automatically find an available charger and reserve it.

[0259] Technical Solution 2: In one aspect, once the vehicle has completed charging beyond a threshold or duration (e.g., a 2-hour limit or a 1-hour reserved charging time), the vehicle initiates a disconnection request to physically disconnect from the charging station. If the vehicle is connected to a special port, the system starts the disconnection procedure (e.g., unlock the connection, gently reverse to disconnect, and move away from the parking space). In one aspect, when using a charging station robot to connect the vehicle to the charging station, the system sends a disconnection message to the robot and unlocks the charging cable. After determining that the robot has successfully disconnected from the cable and moved away from the vehicle, the vehicle can initiate a procedure to release the parking space (which could itself be an invention. For example, such a procedure: scan the area to ensure the vehicle can move without touching other objects, find a new parking space, notify the driver of the new parking space, etc.). In another aspect, when the parking lot is monitored by a human or non-human attendant (e.g., a robot), the system can send a message to the attendant to allow the attendant to disconnect the charging device from the vehicle. The communication can be carried out via Bluetooth, the Internet, or any similar wireless communication (e.g., 4G, 5G, V2X).

[0260] In one aspect, a system is described. Figure 12Illustrates a system for automatically connecting and disconnecting to a charging station according to one or more embodiments. The system includes: a sensor module 1202; and a control module 1204. The control module 1204 includes: a processor 1206; and a memory 1208 communicatively coupled to the processor 1206. The memory 1208 includes a sensor control module that, when executed by the processor 1206, causes the processor 1206 to: scan a vehicle and at least one of one or more images and one or more videos of the vehicle using a computer vision engine (step 1203); retrieve information on a reserved charging session of the vehicle based on the scan (step 1205); transmit a first message to automatically maneuver the vehicle to a reserved charging position (step 1207); transmit a second message to a robotic arm of the reserved charging unit to automatically insert a charger into a charging port of the vehicle and provide a predefined charging amount and a predefined charging duration to the vehicle (step 1209); transmit a third message to the robotic arm of the reserved charging unit to automatically pull out the charger from the charging port after the predefined charging amount and the predefined charging duration are completed for the vehicle (step 1211); and transmit a fourth message to automatically maneuver the vehicle away from the reserved charging position (step 1213).

[0261] In one embodiment, the processor 1206 is operable to determine the specifications of the vehicle based on the scan using an artificial intelligence engine.

[0262] In one embodiment, the processor 1206 is operable to identify a vehicle identifier based on the scan using a computer vision engine. The processor 1206 is also operable to retrieve information on a reserved charging session of the vehicle from a database based on the vehicle identifier.

[0263] In one embodiment, the processor 1206 is also operable to identify a charging port based on the scan using a computer vision engine. In one embodiment, the processor 1206 is also operable to transmit a fifth message to the vehicle to automatically open a charging port door when the charging port is identified.

[0264] In one embodiment, the processor 1206 that determines the specifications of the vehicle based on the scan is operable to determine at least one of a vehicle model, brand, configuration, vehicle type, battery capacity, dimensions, charging port type, charging port location, state of charge, charging sequence, and charging duration.

[0265] In one embodiment, a processor 1206 that uses a computer vision engine to identify a vehicle identifier based on a scan can perform the following technical steps. The processor 1206 performs image analysis on at least one of one or more images and one or more videos of the vehicle using the computer vision engine. The processor 1206 extracts one or more contents from at least one of the one or more images and the one or more videos of the vehicle. The processor 1206 performs natural language processing on the one or more contents using an artificial intelligence engine to interpret the one or more contents as one or more meaningful information. The processor 1206 identifies and discerns a vehicle identification number from the one or more meaningful information.

[0266] In one embodiment, the processor 1206 is also operable to perform the following technical steps: The processor 1206 matches the vehicle identification number with one or more vehicle identification numbers pre-stored in a database. The processor 1206 retrieves the reserved charging session information of the vehicle from the database based on the matching result. In one embodiment, the information of the reserved charging session includes a charging duration, a charging sequence, a charging port type, a charging port location, a charging session start time, a charging session end time, and a predetermined time period.

[0267] In one embodiment, the processor 1206 is operable to perform the following technical steps: Transmit a first message for automatically maneuvering the vehicle to a reserved charging position. The processor 1206 extracts the vehicle type from the vehicle's specifications based on the scan. The processor 1206 determines that the vehicle is an autonomous vehicle based on the vehicle type. The processor 1206 transmits the first message to the electric drive unit of the vehicle to automatically maneuver the vehicle to the reserved charging position. In one embodiment, the electric drive unit is configured to automatically maneuver the vehicle from the coordinates of the vehicle's starting position to the reserved charging position based on the first message.

[0268] In another embodiment, the processor 1206 is operable to perform the following technical steps: Transmit a first message for automatically maneuvering the vehicle to a reserved charging position. The processor 1206 extracts the vehicle type based on a scan from the vehicle's specifications. The processor 1206 determines that the vehicle is a non-autonomous vehicle based on the vehicle type. The processor 1206 transmits the first message to a first robot for automatically maneuvering the vehicle to a reserved charging position. The robot carries the vehicle and moves it to the reserved charging position. In one embodiment, the first message includes at least one of a charging duration, a predetermined time period, the position coordinates of the reserved charging position, the coordinates of the starting position of the vehicle, one or more directions to the reserved charging position, a charging session start time, and a charging session end time. The first robot is configured to perform the following technical steps. The first robot automatically moves to the coordinates of the starting position of the vehicle. The first robot senses the presence of the vehicle by scanning and confirming the vehicle identification number. The first robot automatically aligns to a first predetermined orientation and a first predetermined position relative to the vehicle. The first robot automatically activates one or more load-bearing arms of a hydraulic device to raise and make one or more first predetermined contacts with the vehicle body to lift the vehicle. The first robot automatically activates the hydraulic device of the first robot to lift the vehicle to a first predetermined height above the ground. The first robot automatically maneuvers the vehicle to the reserved charging position based on the first message.

[0269] In one embodiment, the processor 1206 transmits a second message to the robotic arm of the reserved charging unit for automatically inserting a charger into the charging port and providing a predefined charge / electricity to the vehicle for a predefined charging duration. The processor that transmits the second message to the robotic arm performs the following technical steps. The processor 1206 determines whether the vehicle is in a second predefined orientation and a second predefined position relative to the reserved charging unit. The processor 1206 scans the vehicle identification number of the vehicle using a sensor module. The processor 1206 performs image analysis using a computer vision module and matches the vehicle identification number with the information recorded in a database to ensure that the vehicle identification number has a reserved charging session.

[0270] In one embodiment, the processor 1206 is further operable to perform the following technical steps. The processor 1206 identifies the charging port based on image analysis using a computer vision engine. The processor 1206 extracts the coordinates of the charging port. The processor 1206 transmits the second message to the robotic arm of the reserved charging unit for automatically inserting a charger into the charging port. The processor 1206 provides a predefined charge / electricity to the vehicle for a predefined charging duration.

[0271] In one embodiment, the processor 1206 is further operable to determine whether the charging port door is in one of an open state or a closed state. In one embodiment, when the charging port door is in the closed state, the processor 1206 is further operable to transmit a fifth message to the vehicle for opening the charging port door.

[0272] In one embodiment, the processor 1206 transmits a third message to the robotic arm of the reservation charging unit for automatically unplugging the charger by performing the following technical steps. The processor 1206 determines whether the vehicle is in a second predefined orientation and a second predefined position relative to the reservation charging unit. The processor 1206 uses a computer vision engine to identify the charging port by performing image analysis. The processor 1206 extracts the coordinates of the charging port. The processor 1206 transmits the third message to the robotic arm of the reservation charging unit for automatically unplugging the charger from the charging port.

[0273] In one embodiment, the processor 1206 is further operable to determine whether the charging port door is in one of an open state or a closed state when unplugging the charger. When the charging port door is in the open state, the processor 1206 is further operable to send a fifth message to the vehicle for closing the charging port door.

[0274] In one embodiment, the processor 1206 transmits a fourth message for automatically maneuvering the vehicle away from the reservation charging position. The processor 1206 that transmits the fourth message is operable to perform the following technical steps. The processor 1206 extracts the vehicle type from the vehicle's specifications based on a scan. The processor 1206 determines that the vehicle is an autonomous vehicle based on the vehicle type. The processor 1206 transmits the fourth message to the electric drive unit of the vehicle for automatically maneuvering the vehicle away from the reservation charging position.

[0275] In one embodiment, the processor 1206 transmits a fourth message for automatically maneuvering the vehicle away from the reservation charging position. The processor 1206 that transmits the fourth message is operable to perform the following technical steps. The processor 1206 extracts the vehicle type from the vehicle's specifications based on a scan. The processor 1206 determines that the vehicle is a non-autonomous vehicle based on the vehicle type. The processor 1206 transmits the fourth message to the first robot for automatically maneuvering the vehicle away from the reservation charging position.

[0276] In one embodiment, the fourth message includes at least one of a vehicle identification number, a charging duration, a predetermined time period, coordinates of a location of a reserved charging spot, coordinates of a starting location of the vehicle, coordinates of a parking spot, one or more directions to the parking spot, a charging session start time and a charging session end time. In one embodiment, the second message includes at least one of a vehicle identification number, a charging duration, a predetermined time period, coordinates of a location of a charging port, a charging port type, a charging sequence, a charge level, a charging port door operation type, a charging session start time and a charging session end time. In one embodiment, the third message includes at least one of a vehicle identification number, a charging duration, a predetermined time period, coordinates of a location of a charging port, a charging port type, a charging port door operation type, a charging session start time and a charging session end time.

[0277] In one aspect, a method is described. Figure 13 A method for automatically connecting and disconnecting from a charging station according to one or more embodiments is shown. The method includes: using a computer vision engine to scan one of the following: a vehicle and at least one of one or more images and one or more videos of the vehicle (step 1303); retrieving information of a scheduled charging session of the vehicle based on the scan (step 1305); transmitting a first message for automatically manipulating the vehicle to the scheduled charging position (step 1307); transmitting a second message to a mechanical arm of a scheduled charging unit for automatically inserting a charger into a charging port and providing a predefined charge / amount of power to the vehicle for a predefined charging duration (step 1309); transmitting a third message to a mechanical arm of a scheduled charging unit for automatically unplugging the charger from the charging port after the predefined charging duration completes the predefined charging for the vehicle (step 1311); and transmitting a fourth message for automatically manipulating the vehicle away from the scheduled charging position (step 1313).

[0278] In one embodiment, retrieving the scheduled charging session information of the vehicle based on the scan further comprises: using an artificial intelligence engine to determine the specifications of the vehicle based on the scan. In another embodiment, retrieving the scheduled charging session information of the vehicle based on the scan comprises: using a computer vision engine to identify the vehicle identification based on the scan.

[0279] In one embodiment, the method further comprises retrieving information of a scheduled charging session for the vehicle from a database based on the vehicle identification number. In another embodiment, the method further comprises: identifying the charging port based on the scan using a computer vision engine. In another embodiment, the method further comprises: transmitting a fifth message to the vehicle for automatically opening the charging port door after identifying the charging port.

[0280] In one embodiment, the technical steps of determining the specifications of a vehicle using an artificial intelligence engine include: determining at least one of the vehicle model, brand, configuration, vehicle type, battery capacity, size, charging port type, charging port location, charging level, charging sequence, and charging duration.

[0281] In one embodiment, the technical steps of identifying a vehicle identifier based on a scan result using a computer vision engine include: performing image analysis on at least one of one or more images and one or more videos of the vehicle using the computer vision engine; extracting one or more contents from at least one of one or more images and one or more videos of the vehicle; performing natural language processing on the one or more contents using the artificial intelligence engine to interpret the one or more contents as one or more meaningful information; and identifying and recognizing the vehicle identification number from the one or more meaningful information.

[0282] In one embodiment, the method further includes: matching the vehicle identification number with one or more pre-stored vehicle identifications in a database; and retrieving information on the reserved charging session of the vehicle from the database based on the match.

[0283] In one embodiment, the technical steps of transmitting a first message for automatically maneuvering the vehicle to a reserved charging position include: extracting the vehicle type from the vehicle specifications based on the scan; determining that the vehicle is an autonomous vehicle based on the vehicle type; and transmitting the first message to the electric drive unit of the vehicle for automatically maneuvering the vehicle to the reserved charging position.

[0284] In one embodiment, the technical steps of transmitting a first message for automatically maneuvering the vehicle to a reserved charging position include: extracting the vehicle type from the vehicle specifications based on the scan; determining that the vehicle is a non-autonomous vehicle based on the vehicle type; and transmitting the first message to a first robot for automatically maneuvering the vehicle to the reserved charging position.

[0285] In one embodiment, transmitting a second message to the robotic arm of a reserved charging unit for automatically inserting a charger into a charging port and providing a predefined charge / electricity to the vehicle for a predefined charging duration includes: determining whether the vehicle is in a second predefined orientation and a second predefined position relative to the reserved charging unit; scanning the vehicle identification number of the vehicle using a sensor module; and performing image analysis using a computer vision module to ensure that the vehicle identification number is assigned for charging in the reserved charging session.

[0286] In one embodiment, the method further includes: identifying the charging port based on image analysis using a computer vision engine; extracting the coordinates of the charging port; transmitting the second message to the robotic arm of the reserved charging unit for automatically inserting the charger into the charging port; and providing a predefined charge / electricity to the vehicle for a predefined charging duration.

[0287] In one embodiment, the method further includes: determining whether the charging port door is in one of an open state or a closed state. In another embodiment, the method further includes: when the charging port door is in the closed state, transmitting a fifth message to the vehicle for opening the charging port door.

[0288] In one embodiment, after completing a predefined charging of the vehicle for a predetermined charging duration, transmitting a third message to the robotic arm of the reservation charging unit for automatically unplugging the charger includes: determining whether the vehicle is in a second predefined orientation and a second predefined position relative to the reservation charging unit; using a computer vision engine to identify the charging port by performing image analysis; extracting the coordinates of the charging port; and transmitting the third message to the robotic arm of the reservation charging unit for automatically unplugging the charger from the charging port.

[0289] In one embodiment, the method further includes: determining whether the charging port door is in one of an open state or a closed state when unplugging the charger. In another embodiment, the method further includes: when the charging port door is in the open state, sending a fifth message to the vehicle for closing the charging port door.

[0290] In one embodiment, transmitting a fourth message for automatically maneuvering the vehicle away from the reservation charging position includes the following technical steps: extracting the vehicle type from the vehicle's specifications based on a scan; determining that the vehicle is an autonomous vehicle based on the vehicle type; and transmitting the fourth message to the electric drive unit of the vehicle for automatically maneuvering the vehicle away from the reservation charging position.

[0291] In one embodiment, transmitting a fourth message for automatically maneuvering the vehicle away from the reservation charging position includes the following technical steps: extracting the vehicle type from the vehicle's specifications based on a scan; determining that the vehicle is a non-autonomous vehicle based on the vehicle type; and transmitting the fourth message to the first robot for automatically maneuvering the vehicle away from the reservation charging position.

[0292] In another aspect, a non-transitory computer-readable storage medium is described. Figure 14A non-transitory computer-readable storage medium according to one or more embodiments is shown. The non-transitory computer-readable storage medium includes a series of instructions that, when executed by a processor, cause: scanning a vehicle and at least one of one or more images and one or more videos of the vehicle using a computer vision engine (step 1403); retrieving information about a reserved charging session of the vehicle based on the scan (step 1405); transmitting a first message to automatically maneuver the vehicle to a reserved charging position (step 1407); transmitting a second message to a robotic arm of a reserved charging unit to automatically insert a charger into a charging port and provide a predefined charge / electricity amount to the vehicle for a predefined charging duration (step 1409); transmitting a third message to the robotic arm of the reserved charging unit to automatically remove the charger from the charging port after completing a predefined charge of the vehicle for the predefined charging duration (step 1411); and transmitting a fourth message to automatically maneuver the vehicle away from the reserved charging position (step 1413).

[0293] In one embodiment, transmitting the first message to automatically maneuver the vehicle to a reserved charging position causes: extracting a vehicle type from the vehicle's specifications based on the scan; determining that the vehicle is an autonomous vehicle based on the vehicle type; and transmitting the first message to an electric drive unit of the vehicle to automatically maneuver the vehicle to the reserved charging position.

[0294] In one embodiment, transmitting the second message to the robotic arm of the reserved charging unit to automatically insert the charger into the charging port and provide a predefined charge / electricity amount to the vehicle for a predefined charging duration further causes: determining whether the vehicle is in a second predefined orientation and a second predefined position relative to the reserved charging unit; scanning a vehicle identification of the vehicle; and performing image analysis using a computer vision module to ensure that the vehicle identification is assigned for charging of the reserved charging session.

[0295] In one embodiment, the non-transitory computer-readable storage medium further causes: identifying a charging port based on image analysis using a computer vision engine; extracting coordinates of the charging port; transmitting the second message to the robotic arm of the reserved charging unit to automatically insert the charger into the charging port; and providing a predefined charge / electricity amount to the vehicle for a predefined charging duration.

[0296] In one embodiment, after completing a predefined charge of the vehicle for a predefined charging duration, transmitting the third message to the robotic arm of the reserved charging unit to automatically remove the charger causes: determining whether the vehicle is in a second predefined orientation and a second predefined position relative to the reserved charging unit; identifying the charging port using the computer vision engine by performing image analysis; extracting coordinates of the charging port; and transmitting the third message to the robotic arm of the reserved charging unit to automatically remove the charger from the charging port.

[0297] In one embodiment, transmitting a fourth message to automatically maneuver a vehicle away from a reserved charging position causes: extracting a vehicle type based on a scan from the vehicle's specifications; determining that the vehicle is an autonomous vehicle based on the vehicle type; and transmitting the fourth message to the vehicle's electric drive unit to automatically maneuver the vehicle away from the reserved charging position.

[0298] For example, Figure 15 FIG. shows a robotic arm inserting and removing a charger into and out of a charging port of a vehicle 1500 according to one or more embodiments. Once the vehicle is maneuvered into the charging position, the robotic arm of the charging device maneuvers the charger plug into the charging port. The charging device includes a robotic device that includes the robotic arm. The charging plug is securely fixed to the charging port to provide power to charge the vehicle's battery pack. In one embodiment, the charger plug can be a charging plate and the charging port can be a charging panel. The robotic arm maneuvers the charging plate relative to the vehicle's charging panel. In one embodiment, the charging device can include one or more robotic arms.

[0299] The charging plate 1520 is positioned at a desired or optional separation distance from the charging panel, which is assisted by a separation distance sensor 1527 on the charging plate 1520. The charging plate 1520 can maintain a limited separation distance 1508 from the charging panel 1518 or can be in direct contact with the charging panel (i.e., such that the separation distance 1508 is zero). Charging can occur inductively. In another embodiment, the separation distance sensor 1527 can alternatively or additionally be provided on the robotic unit arm 1504. The vehicle 1500 receives charging through the charging panel 1518, which in turn charges the energy storage unit 1512. The charging panel controller 1510 communicates with any one of the elements in the energy storage unit 1512, the charging panel 1518, the vehicle database 1513, the charging provision controller 1522, and / or the dashboard of the charging provision controller (including a power management display and a charging manual controller). The vehicle database 1513 can include a robotic unit charging data structure 1534.

[0300] The robotic unit communicates with and / or is interconnected to the charging provision controller 1522, the power supply 1516, and the robotic unit database 1517. The power supply 1516 supplies power, such as electricity, to the charging plate 1520 to charge the vehicle through the charging panel 1518. The controller 1524 directly and / or fully maneuvers or operates the robotic unit or, in one embodiment, maneuvers or operates the robotic unit with the assistance of a charging manual controller by a remote user (e.g., a driver or passenger in the vehicle).

[0301] The charging panel 1518 of the vehicle can be located anywhere on the vehicle, such as including the roof, side panels, trunk, hood, front bumper or rear bumper of the vehicle, as well as the wheels. In some embodiments, the charging panel 1518 can be deployable, i.e., it can extend or be deployed only when charging is required. For example, the charging panel 1518 can generally be flush with the roof of the vehicle and extend when charging is needed. Similarly, in one embodiment, the charging plate 1520 can be not connected to the robotic unit and / or the robotic unit arm 1504, but can be mounted, for example, on the base of the robotic unit. The robotic unit arm 1504 can be configured to manipulate the charging plate 1520 to any position on the charging panel 1518 of the vehicle so as to enable charging. The control of the charging and / or the positioning of the charging plate 1520 can be manual, automatic or semi-automatic; the control can be performed by receiving a GUI power management display used by the driver or passenger of the vehicle, and / or a charging operator associated with the power source 1516 and / or the robotic unit.

[0302] In some embodiments, the robotic unit is configured to also perform additional services other than battery charging. More specifically, the robotic unit can perform any vehicle maintenance service that is traditionally performed at a vehicle service station, such as inspection, repair, and / or replacement of parts (e.g., electrical or magnetic induction coils, entire battery units or their components), upgrading of parts and / or software, and other services known to those skilled in the art.

[0303] As an example, Figure 16a A first message according to one or more embodiments is shown. When the vehicle is an autonomous vehicle, the first message is transmitted to the vehicle. When the vehicle is a non-autonomous vehicle, the first message is transmitted to an external robot. The first message is adapted to automatically maneuver the vehicle from its current position to a reserved charging location. The first message includes at least one of a vehicle ID, a charging duration, a predetermined time period, the coordinates of the location of the reserved charging location, the coordinates of the starting position of the vehicle, one or more directions to the reserved charging location, a charging session start time, and a charging session end time.

[0304] The vehicle ID can be a serial identification number or a tag associated with the electric vehicle, which is configured to identify, recognize, and locate the vehicle. The coordinates of the vehicle position represent the current position of the vehicle. The coordinates of the reserved charging location represent the current position of the reserved charging location. The predetermined time period represents the range from the start time to the end time of the charging session. The charging duration refers to the total time of the predetermined charging session. The one or more directions to the reserved charging location represent one or more routes to the reserved charging location. The charging session start time represents the start time of the charging session. The charging session end time represents the end / completion time of the charging session.

[0305] As an example, Figure 16bShows a fourth message according to one or more embodiments. When the vehicle is an autonomous vehicle, the fourth message is transmitted to the vehicle. When the vehicle is a non-autonomous vehicle, the fourth message is transmitted to an external robot. The fourth message is adapted to automatically maneuver the vehicle away from a reserved charging position. The fourth message includes at least one of a vehicle ID, a charging duration, a predetermined time period, coordinates of the location of the reserved charging position, coordinates of the location of the parking space, one or more directions to the parking space, a charging session start time, and a charging session end time.

[0306] The vehicle ID can be a serial identification number or a tag associated with the electric vehicle, which is configured to identify, recognize, and locate the vehicle. The coordinates of the vehicle location indicate the current location of the vehicle. The coordinates of the location of the reserved charging position indicate the current location of the reserved charging position. The predetermined time period indicates the range from the start time to the end time of the charging session. The charging duration refers to the total time of the predetermined charging session. One or more directions to the reserved charging position indicate one or more routes to the reserved charging position. The charging session start time indicates the start time of the charging session. The end time of the charging session indicates the end / completion time of the charging session.

[0307] As an example, Figure 17a Shows a second message according to one or more embodiments. The second message is transmitted to the robotic arm of the reserved charging unit to automatically insert the charger into the charging port of the vehicle. The second message is transmitted to the robotic arm regardless of whether the vehicle is an autonomous vehicle or a non-autonomous vehicle. The second message includes at least one of a vehicle identification (ID) number, a charging duration, a predetermined time period, coordinates of the location of the charging port, a charging port type, a charging sequence, a charging level, an operation type of the charging port door, a charging session start time, and a charging session end time.

[0308] The vehicle ID number can be a serial identification number or a tag associated with the electric vehicle, which is configured to identify, recognize, and locate the vehicle. The coordinates of the location of the charging port indicate the current orientation and current location of the charging port. The predetermined time period indicates the range from the start time to the end time of the charging session. The charging duration refers to the total time of the predetermined charging session. The charging session start time indicates the start time of the charging session. The charging session end time indicates the end / completion time of the charging session. The charging port type refers to one of a charging panel or a charger socket. The charging sequence indicates one of normal charging, fast charging, and trickle charging. The charging level indicates one of level 1 charging, level 2 charging, and level 3 charging. The operation type of the charging port door indicates one of a sliding type or a door type.

[0309] As an example, Figure 17bShows a third message according to one or more embodiments. The third message is transmitted to the robotic arm of the reservation charging unit for automatically pulling out the charger from the charging port of the vehicle. Whether the vehicle is an autonomous vehicle or a non-autonomous vehicle, the third message will be transmitted to the robotic arm. The third message includes at least one of vehicle identification, charging duration, predetermined time period, charging port position coordinates, charging port type, operation type of the charging port door, charging session start time, and charging session end time.

[0310] The vehicle ID number can be a serial identification number or a tag associated with the electric vehicle, which is configured to identify, recognize, and locate the vehicle. The position coordinates of the charging port represent the current position and the current location of the charging port. The predetermined time period represents the range from the start time to the end time of the charging session. The charging duration refers to the total time of the predetermined charging session. The charging session start time represents the start time of the charging session. The charging session end time represents the end / completion time of the charging session. The charging port type represents one of the charging panel or the charger socket. The operation type of the charging port door represents one of the sliding type or the door type.

[0311] Figure 18 Shows a vehicle scan according to one or more embodiments. In one embodiment, the vehicle is approaching a reserved charging station. The sensor module 1802 can be installed on the infrastructure. The infrastructure can be located along the vehicle's route. The infrastructure can be a bridge, an underpass, a traffic signal pole, a building, etc. along the vehicle's route. The infrastructure can also be located on the charging station. The sensor module 1802 includes one or more sensors integrated for scanning and identifying the vehicle. The one or more sensors include one or more cameras, one or more radar sensors, one or more automatic license plate recognition sensors, one or more vision sensors, one or more ultrasonic sensors, etc.

[0312] The sensor module 1802 scans the vehicle and identifies the identity of the vehicle by scanning the vehicle identification number. The processor receives the scanned information and further processes it to identify the identity of the vehicle. The processor receives the scanned information and further processes it to determine the specifications of the vehicle. In one embodiment, the processor determines at least one of the vehicle model, brand, configuration, vehicle type, battery capacity, size, charging port type, charging port position, state of charge, charging sequence, and charging duration according to the specifications. The sensor module 1802 can also include a weight sensor, a weighing sensor, etc. to determine the weight of the vehicle.

[0313] In one embodiment, the sensor module 1802 captures one or more images or one or more videos of the vehicle. The processor performs image analysis on at least one of the one or more images and the one or more videos of the vehicle using a computer vision engine. Then, the processor extracts one or more contents from at least one of the one or more images and the one or more videos of the vehicle. Then, the processor performs natural language processing on the one or more contents using an artificial intelligence engine to interpret the one or more contents as one or more meaningful information. Then, the processor identifies and discriminates a vehicle identifier from the one or more meaningful information.

[0314] In another aspect, a vehicle is described. Figure 19 A vehicle that automatically connects and disconnects from a charging station according to one or more embodiments is shown. The vehicle includes a sensor module 1902 and a control module 1904. The control module 1904 includes a processor 1906 and a memory 1908 communicatively coupled to the processor 1906. The memory 1908 includes a sensor control module, and when the processor 1906 executes the module, the processor 1906 will: determine whether the state of charge of the vehicle is below a threshold state of charge level (step 1903); when the state of charge of the vehicle is below the threshold state of charge level, retrieve information about a scheduled charging session of the vehicle (step 1905); transmit a first message to automatically maneuver the vehicle to a scheduled charging position (step 1907); transmit a second message to a robotic arm of the scheduled charging unit to automatically insert a charger into a charging port and provide a predefined charge to the vehicle for a predefined charging duration (step 1909); transmit a third message to the robotic arm of the scheduled charging unit to automatically remove the charger from the charging port after the predefined charge for the vehicle is completed for the predefined charging duration (step 1911); and transmit a fourth message to automatically maneuver the vehicle away from the scheduled charging position (step 1913).

[0315] In one embodiment, with respect to transmitting the first message to automatically maneuver the vehicle to a scheduled charging position, the processor 1906 is operable to: when the vehicle is an autonomous vehicle, transmit the first message to an electric drive unit of the vehicle to automatically maneuver the vehicle to a scheduled charging position.

[0316] In one embodiment, with respect to transmitting the first message to automatically maneuver the vehicle to a scheduled charging position, the processor 1906 is operable to: when the vehicle is a non-autonomous vehicle, transmit the first message to a first robot to automatically maneuver the vehicle to a scheduled charging position.

[0317] In one embodiment, the first message includes at least one of a charging duration, a scheduled time period, position coordinates of a scheduled charging position, coordinates of a starting position of the vehicle, one or more directions to the scheduled charging position, a charging session start time, and a charging session end time.

[0318] In one embodiment, the first robot is configured to automatically move to the coordinates of the starting position of the vehicle, sense the presence of the vehicle by scanning and verifying the vehicle identification number, automatically align to a first predetermined position and a first predetermined orientation relative to the vehicle, automatically activate one or more load-bearing arms of the hydraulic unit to raise the vehicle body, make one or more first predetermined contacts with the vehicle body to lift the vehicle, automatically activate the hydraulic unit of the first robot to lift the vehicle to a first predetermined height above the ground, and automatically maneuver the vehicle to a reserved charging position based on the first message.

[0319] In one aspect, a method is described. Figure 20 A method according to one or more embodiments is shown. The method includes: determining whether the state of charge of the vehicle is below a threshold state of charge level (step 2003); when the state of charge of the vehicle is below the threshold state of charge level, retrieving information of a reserved charging session of the vehicle (step 2005); transmitting a first message to automatically maneuver the vehicle to a reserved charging position (step 2007); transmitting a second message to a robotic arm of a reserved charging unit to automatically insert a charger into a charging port and provide a predefined charge to the vehicle for a predefined charging duration (step 2009); transmitting a third message to the robotic arm of the reserved charging unit to automatically pull out the charger from the charging port after completing the predefined charge for the vehicle for the predefined charging duration (step 2011); and transmitting a fourth message to automatically move the vehicle away from the reserved charging position (step 2013).

[0320] In one embodiment, transmitting a first message to automatically maneuver the vehicle to a reserved charging position includes: when the vehicle is an autonomous vehicle, transmitting the first message to an electric drive unit of the vehicle to automatically maneuver the vehicle to a reserved charging position.

[0321] In one embodiment, transmitting a first message to automatically maneuver the vehicle to a reserved charging position includes: when the vehicle is a non-autonomous vehicle, transmitting the first message to a first robot to automatically maneuver the vehicle to a reserved charging position.

[0322] In one embodiment, the first message includes at least one of a charging duration, a predetermined time period, coordinates of the position of the reserved charging position, coordinates of the starting position of the vehicle, one or more directions to the reserved charging position, a charging session start time, and a charging session end time.

[0323] In one embodiment, the first robot is configured to automatically move to the coordinates of the starting position of the vehicle; sense the presence of the vehicle by scanning and confirming the vehicle identification; automatically align to a first predefined orientation and a first predefined position relative to the vehicle; automatically activate one or more load-bearing arms of the hydraulic device to raise the vehicle body and make one or more first predefined contacts with the vehicle body to lift the vehicle; automatically activate the hydraulic device of the first robot to lift the vehicle to a first predefined height above the ground; and automatically maneuver the vehicle to a reserved charging position based on the first message.

[0324] In one aspect, a non-transitory computer-readable storage medium is described. Figure 21 A non-transitory computer-readable storage medium according to one or more embodiments is shown. The non-transitory computer-readable storage medium includes a series of instructions that, when executed by a processor, cause: determining whether the state of charge of the vehicle is below a threshold state of charge level (step 2103); when the state of charge of the vehicle is below the threshold state of charge level, retrieving information about a reserved charging session of the vehicle (step 2105); transmitting a first message to automatically maneuver the vehicle to a reserved charging position (step 2107); transmitting a second message to the robotic arm of the reserved charging unit to automatically insert a charger into the charging port and provide a predefined charge / electricity amount to the vehicle for a predefined charging duration (step 2109); transmitting a third message to the robotic arm of the reserved charging unit to automatically remove the charger from the charging port after a predefined charge for a predefined charging duration of the vehicle is completed (step 2111); and transmitting a fourth message to automatically maneuver the vehicle away from the reserved charging position (step 2113).

[0325] In one embodiment, transmitting a first message to automatically maneuver the vehicle to a reserved charging position causes: when the vehicle is an autonomous vehicle, transmitting the first message to the electric drive unit of the vehicle to automatically maneuver the vehicle to a reserved charging position.

[0326] In one embodiment, transmitting a first message to automatically maneuver the vehicle to a reserved charging position causes: when the vehicle is a non-autonomous vehicle, transmitting the first message to the first robot to automatically maneuver the vehicle to a reserved charging position.

[0327] In one embodiment, the first message includes at least one of a charging duration, a predefined time period, the position coordinates of the reserved charging position, the starting position coordinates of the vehicle, one or more directions to the reserved charging position, a charging session start time, and a charging session end time.

[0328] Technical Problem 3: The problem is that the vehicle needs to be charged and there is no available charging station at the current location. This can be due to various reasons, including the driver not reserving a parking space, someone occupying the parking space without reservation, or the reserved charging station not being fully operational. In any case, the driver wants to find a charging station. Therefore, a charging station locator needs to be included.

[0329] Technical Solution 3: On the one hand, each electric vehicle is equipped with a Charging Station Locator (CSL). The CSL continuously monitors the locations of all available charging stations. When the vehicle approaches a charging station, the CSL will network connect (ping) the reserved charging station to determine its operational status and occupancy status. If the operational status is clear and the charging station location is unoccupied, the charging station is highlighted and directions are provided. In one aspect, the charging station directions are magnified at the charging station location. However, if there are no available charging stations in the desired or nearest set of charging stations (CS), the CSL identifies the next closest CS to the desired destination. The identified CS can be based on the available charge.

[0330] In one aspect, a system is described. Figure 22 A system for automatically locating available chargers according to one or more embodiments is shown. The system includes a Charging Station Locator 2202. The Charging Station Locator 2202 includes a memory 2208 and a processor 2206 communicatively coupled to the memory 2208. The processor 2206 is operable to: monitor one or more charging stations located within a predefined distance from the vehicle (step 2203); determine whether the vehicle is within a predefined proximity of a reserved charging station among the one or more charging stations (step 2205); transmit a first status query to the reserved charging station (step 2207); receive a first message including at least one of a first operational status and a first occupancy status of the reserved charging station in response to the first status query (step 2209); provide one or more first routes to the reserved charging station on a display when the first operational status and the first occupancy status are available (step 2211); and determine a subsequent charging station and provide one or more second routes to the subsequent charging station on the display when at least one of the first operational status and the first occupancy status is occupied (step 2213).

[0331] In one embodiment, the processor 2206 is operable to: determine a subsequent charging station based on the state of charge of one or more batteries associated with the vehicle. In another embodiment, the processor 2206 is operable to: determine a subsequent charging station based on the route traveled by the vehicle. In another embodiment, the processor 2206 is operable to: determine a subsequent charging station based on the itinerary of the user riding in the vehicle. In another embodiment, the processor 2206 is operable to: determine a subsequent charging station based on a second operational status and a second occupancy status of the subsequent charging station. The subsequent charging station is the next closest charging station.

[0332] In one embodiment, the processor 2206 monitors one or more charging stations located within a predefined distance from the vehicle and may perform the following technical steps. The processor 2206 determines the real-time position of the vehicle using one or more sensors associated with the vehicle. The processor 2206 uses an artificial intelligence engine to determine one or more areas within a predefined distance around the real-time position of the vehicle, the one or more areas including one or more charging stations. The processor 2206 identifies one or more charging stations located within the one or more areas within a predefined distance from the vehicle. The processor 2206 monitors the positions of the one or more charging stations identified within a predefined distance from the vehicle.

[0333] In one embodiment, the processor 2206 that monitors one or more charging stations located within a predefined distance from the vehicle is operable to perform the following technical steps. The processor 2206 determines the real-time position of the vehicle using one or more sensors associated with one or more external infrastructures on the vehicle route. The processor 2206 uses an artificial intelligence engine to determine one or more areas within a predefined distance around the real-time position of the vehicle, the one or more areas including one or more charging stations. The processor 2206 identifies one or more charging stations located within the one or more areas within a predefined distance from the vehicle. The processor 2206 monitors the positions of the one or more charging stations identified within a predefined distance from the vehicle.

[0334] In one embodiment, in determining whether the vehicle is within a predefined proximity of a reserved charging station among one or more charging stations, the processor 2206 is operable to perform the following technical steps. The processor 2206 determines the real-time position of the vehicle using one or more sensors associated with the vehicle and one of one or more external infrastructures on the vehicle route. The processor 2206 determines the real-time position of the reserved charging station. The processor 2206 matches the real-time position of the vehicle with the real-time position of the reserved charging station. The processor 2206 determines whether the vehicle is within a predefined proximity of the reserved charging station based on the offset between the real-time position of the vehicle and the real-time position of the reserved charging station.

[0335] In one embodiment, when the reserved charging station has completed the charging operation for the previous vehicle and is available for charging the vehicle, the first operating state of the reserved charging station is received as available. In another embodiment, when the reserved charging station has completed the charging operation for the previous vehicle and the previous vehicle has left the reserved charging station, making the reserved charging station available for charging the vehicle, the first occupancy state of the reserved charging station is received as available.

[0336] In another embodiment, when the reserved charging station is charging the previous vehicle and is unavailable, the first operating state of the reserved charging station is received as occupied.

[0337] In one embodiment, when a reserved charging station is charging a previous vehicle and the previous vehicle blocks the reserved charging station, resulting in the unavailability of the reserved charging station, the first occupancy status of the reserved charging station received is occupied.

[0338] In one embodiment, the display is associated with one of the vehicle's infotainment unit and the user's external device.

[0339] In one embodiment, when the first operation status and the first occupancy status are received as available, the processor 2206 provides one or more first routes to the reserved charging station, and the processor can perform the following technical steps. When the first operation status and the first occupancy status are received as available, the processor 2206 determines that the reserved charging station is available for charging the vehicle. The processor 2206 uses one or more sensors associated with the vehicle and one of one or more external infrastructures on the vehicle route to determine the real-time position of the vehicle. The processor 2206 retrieves the real-time position of the reserved charging station from the database. The processor 2206 identifies one or more first routes leading from the real-time position of the vehicle to the real-time position of the reserved charging station. The processor 2206 provides one or more first routes to the display.

[0340] In one embodiment, when at least one of the first operation status and the first occupancy status is received as occupied, the processor 2206 is operable to determine that the reserved charging station is not available for charging the vehicle.

[0341] In one embodiment, the processor 2206 can also perform the following technical steps. The processor 2206 uses one or more sensors associated with the vehicle and one of one or more external infrastructures on the vehicle route to determine the real-time position of the vehicle. The processor 2206 identifies a subsequent charging station among one or more charging stations within a predefined distance of the vehicle. The processor 2206 transmits a second status query to the subsequent charging station. The processor 2206 receives a second message in response to the second status query, and the second message includes at least one of the second operation status and the second occupancy status of the subsequent charging station. When the second operation status and the second occupancy status are received as available, the processor 2206 determines that the subsequent charging station is available for charging the vehicle.

[0342] In one embodiment, the processor 2206 can also perform the following technical steps: The processor 2206 retrieves the real-time position of the subsequent charging station from the database; The processor 2206 identifies one or more second routes leading from the real-time position of the vehicle to the real-time position of the subsequent charging station according to the real-time position of the vehicle; The processor 2206 displays one or more second routes leading to the subsequent charging station on the display.

[0343] In one aspect, a method is described. Figure 23A method according to one or more embodiments is shown. The method includes: monitoring one or more charging stations within a predefined distance from the vehicle (step 2303); determining whether the vehicle is within a predefined distance from a reserved charging station among the one or more charging stations (step 2305); transmitting a first status query to the reserved charging station (step 2307); receiving, in response to the first status query, a first message including at least one of a first operating status and a first occupancy status of the reserved charging station (step 2309); when the first operating status and the first occupancy status are available, providing one or more first routes to the reserved charging station on a display (step 2311); and determining a subsequent charging station and providing one or more second routes to the subsequent charging station on the display when at least one of the first operating status and the first occupancy status is occupied (step 2313).

[0344] In one embodiment, monitoring one or more charging stations within a predefined distance from the vehicle further includes: determining a real-time position of the vehicle using one or more sensors associated with the vehicle; determining, using an artificial intelligence engine, one or more areas around the real-time position of the vehicle for the predefined distance that include one or more charging stations; identifying one or more charging stations within one or more of the areas within the predefined distance from the vehicle; and monitoring the positions of the one or more identified charging stations within the predefined distance from the vehicle.

[0345] In one embodiment, monitoring one or more charging stations within a predefined distance from the vehicle further includes: determining a real-time position of the vehicle using one or more sensors associated with one or more external infrastructures along the vehicle route; determining, using an artificial intelligence engine, one or more areas around the real-time position of the vehicle for the predefined distance that include one or more charging stations; identifying one or more charging stations within one or more of the areas within the predefined distance from the vehicle; and monitoring the positions of the one or more identified charging stations within the predefined distance from the vehicle.

[0346] In one embodiment, determining whether the vehicle is within a predefined proximity to a reserved charging station among the one or more charging stations further includes: determining a real-time position of the vehicle using one or more sensors associated with the vehicle and one of the one or more external infrastructures on the vehicle travel route; determining a real-time position of the reserved charging station; matching the real-time position of the vehicle and the real-time position of the reserved charging station; and determining whether the vehicle is within the predefined proximity to the reserved charging station based on an offset between the real-time position of the vehicle and the real-time position of the reserved charging station.

[0347] In one embodiment, when the first operation status and the first occupancy status are received as available, providing one or more first routes to a reserved charging station on a display further includes: when the first operation status and the first occupancy status are received as available, determining that the reserved charging station is available for charging the vehicle; using one or more sensors associated with the vehicle and one of one or more external infrastructures on the vehicle route to determine the real-time position of the vehicle; retrieving the real-time position of the reserved charging station from a database; identifying one or more first routes leading to the real-time position of the reserved charging station based on the real-time position of the vehicle; and providing one or more first routes to the reserved charging station on the display.

[0348] In one embodiment, when at least one of the received first operation status and the first occupancy status is occupied, determining a subsequent charging station and providing one or more second routes to the subsequent charging station on the display further includes: when at least one of the received first operation status and the first occupancy status is occupied, determining that the reserved charging station is not available for charging the vehicle.

[0349] In one embodiment, when at least one of the first operation status and the first occupancy status is occupied, determining a subsequent charging station and providing one or more second routes to the subsequent charging station on the display further includes: using one or more sensors associated with the vehicle and one of one or more external infrastructures on the vehicle route to determine the real-time position of the vehicle; identifying a subsequent charging station among one or more charging stations within a predefined distance of the vehicle; transmitting a second status query to the subsequent charging station; in response to the second status query, receiving a second message including at least one of a second operation status and a second occupancy status of the subsequent charging station; and when the second operation status and the second occupancy status are received as available, determining that the subsequent charging station is available for charging the vehicle.

[0350] In one embodiment, when at least one of the first operation status and the first occupancy status is occupied, determining a subsequent charging station and providing one or more second routes to the subsequent charging station on the display further includes: retrieving the real-time position of the subsequent charging station from a database; identifying one or more second routes leading to the real-time position of the subsequent charging station based on the real-time position of the vehicle; and providing one or more second routes to the subsequent charging station on the display.

[0351] In one aspect, a non-transitory computer-readable storage medium is described. Figure 24A non-transitory computer-readable storage medium according to one or more embodiments is shown. The non-transitory computer-readable storage medium includes a series of instructions that, when executed by a processor, cause: monitoring one or more charging stations located within a predefined distance from the vehicle (step 2403); determining whether the vehicle is within a predefined distance from a reserved charging station among the one or more charging stations (step 2405); transmitting a first status query to the reserved charging station (step 2407); receiving, in response to the first status query, a first message including at least one of a first operating status and a first occupancy status of the reserved charging station (step 2409); providing, when the first operating status and the first occupancy status are available, one or more first routes to the reserved charging station on a display (step 2411); and determining a subsequent charging station and providing one or more second routes to the subsequent charging station on the display when at least one of the first operating status and the first occupancy status is occupied (step 2413).

[0352] In one embodiment, determining a subsequent charging station and providing one or more second routes to the subsequent charging station on the display causes: when at least one of the first operating status and the first occupancy status is occupied, determining that the reserved charging station is not available for charging the vehicle.

[0353] In one embodiment, determining a subsequent charging station and providing one or more second routes to the subsequent charging station on the display also causes the execution of the following technical steps. The non-transitory computer-readable storage medium uses one or more sensors associated with the vehicle and one of one or more external infrastructures on the vehicle route to determine the real-time position of the vehicle. The non-transitory computer-readable storage medium causes the identification of a subsequent charging station among the one or more charging stations within a predefined distance from the vehicle. Then, the non-transitory computer-readable storage medium causes the transmission of a second status query to the subsequent charging station. Then, the non-transitory computer-readable storage medium causes the receipt of a second message including at least one of a second operating status and a second occupancy status of the subsequent charging station in response to the second status query. Then, when the second operating status and the second occupancy status are available, the non-transitory computer-readable storage medium determines that the subsequent charging station is available for charging the vehicle.

[0354] In one embodiment, determining a subsequent charging station and providing one or more second routes to the subsequent charging station on the display also causes the execution of the following technical steps. The non-transitory computer-readable storage medium causes the retrieval of the real-time position of the subsequent charging station from a database; identifying one or more second routes leading from the real-time position of the vehicle to the real-time position of the subsequent charging station. Then, the non-transitory computer-readable storage medium causes the provision of one or more second routes to the subsequent charging station on the display.

[0355] By way of example,Figure 25 shows a first message described in Figure 22 one or more embodiments. The first message includes one of a charging station identification number, charging station location coordinates, operating status, occupancy status, charging date, charging session start time, charging session end time, predetermined time period, and charging duration.

[0356] The charging station identification number may be a sequence identification number or a tag associated with the charging station, the tag being configured to identify, recognize, and locate the charging station. The coordinates of the charging station location indicate the location of the charging station. The charging date indicates the date on which the charging session is scheduled. The charging session start time indicates the start time of the charging session. The charging session end time indicates the end / completion time of the charging session. The predetermined time period indicates the range from the start time to the end time of the charging session. The charging duration refers to the total time for which the charging session is scheduled. The operating status may be one of "available" and "occupied". When the charging station is charging another vehicle, the operating status is indicated as "occupied". When there is no charging session reserved for a vehicle at the charging station, the operating status may also be indicated as "occupied". When the charging station is ready to charge a vehicle, the operating status is indicated as "available". When a charging session is reserved for a vehicle at the charging station, the operating status may also be indicated as "available". The occupancy status may be one of "available" and "occupied". When another vehicle blocks or obstructs the charging station, the occupancy status is indicated as "occupied". When a charging session is reserved for a vehicle at the charging station, the occupancy status may also be indicated as "occupied". When no other vehicle blocks or obstructs the charging station, the occupancy status is indicated as "available". When a charging session is reserved for a vehicle at the charging station, the occupancy status may also be indicated as "available".

[0357] Figure 26 shows the determination of a subsequent charging station 2606 according to one or more embodiments. The processor monitors one or more charging stations located within a predefined distance of the vehicle. The processor then determines whether the vehicle is within a predefined proximity 2602 of a reserved charging station 2604 among the one or more charging stations. After determining that the vehicle is within the predefined proximity 2602 of the reserved charging station 2604, the processor transmits a first status query to the reserved charging station 2604. The processor then receives a first message in response to the first status query, the first message including at least one of a first operating status and a first occupancy status of the reserved charging station 2604. When the first operating status and the first occupancy status are received as available, the processor provides one or more first routes to the reserved charging station 2604 to the display. When at least one of the first operating status and the first occupancy status is received as occupied, the processor determines a subsequent charging station 2606 and provides one or more second routes to the subsequent charging station 2606 to the display.

[0358] Figure 27Shows one or more areas 2702 containing charging stations determined according to one or more embodiments. The processor uses one or more sensors associated with the vehicle to identify the real-time position of the vehicle. Then, the processor uses an artificial intelligence engine to determine one or more areas 2702 including one or more charging stations around the real-time position of the vehicle for a predefined distance. Then, the processor identifies one or more charging stations within one or more areas located within a predefined distance from the vehicle. The one or more areas 2702 can be grouped into a geographical range 2704. The one or more sensors can be associated with the vehicle or with one or more external infrastructures located along the vehicle route.

[0359] Figure 28 Shows one or more routes 2806 to a reserved charging station 2802 according to one or more embodiments. When it is received that the first operation state and the first occupancy state are available, the processor determines that the reserved charging station 2802 is available for charging the vehicle. Then, the processor uses one or more sensors associated with the vehicle and one of the one or more external infrastructures on the vehicle route to determine the real-time position of the vehicle. Then, the processor retrieves the real-time position of the reserved charging station 2802 from the database. Then, the processor identifies one or more routes 2806 from the real-time position of the vehicle to the real-time position of the reserved charging station 2802. Then, the processor provides one or more routes 2806 to the reserved charging station 2802 to the display. When it is received that at least one of the first operation state and the first occupancy state of the reserved charging station 2802 is occupied, the processor can determine a subsequent charging station 2804.

[0360] Figure 29 Shows one or more routes 2908 to a subsequent charging station 2904 according to one or more embodiments. When it is determined that the reserved charging station 2902 is not available for charging the vehicle, the processor retrieves the real-time position of the subsequent charging station 2904 from the database. Then, the processor identifies one or more routes 2908 from the real-time position of the vehicle to the real-time position of the subsequent charging station 2904. Then, the processor provides one or more routes 2908 to the subsequent charging station 2904 to the display.

[0361] In one embodiment of the system, a machine learning model is configured to learn using labeled data using 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.

[0362] In one embodiment of the system, the machine learning model is configured to learn from real-time data using unsupervised learning methods, and the unsupervised learning methods include the logic of using at least one of k-means clustering, hierarchical clustering, hidden Markov models, and prior algorithms.

[0363] In one embodiment of the system, the machine learning model has a feedback loop, and 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.

[0364] In one embodiment of the system, the machine learning model includes a recurrent neural network model.

[0365] In one embodiment of the system, the machine learning model has a feedback loop, and further reinforcement learning is carried out by rewarding each true positive of the system output.

[0366] Figure 30A The structure of a neural network / machine learning model with a feedback loop is shown. The 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 associated weights and thresholds. If the output of any single node is higher than the specified threshold, the node is activated and the data is sent to the next layer of the network. Otherwise, no data is passed to the next layer of the network. The 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 prior algorithms. The output layer can predict or detect a first characteristic, a second characteristic, the tightness of a seat belt, a score, a convenience score, etc. according to the input data (as described above).

[0367] In one embodiment, the ANN can be a deep neural network (DNN), which is a multi-layer neural network in series, including artificial neural network (ANN), convolutional neural network (CNN), and 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 commonly used for ordinal or time problems, such as language translation, natural language processing (NLP), speech recognition, and image recognition. Like feedforward and convolutional neural networks (CNN), recurrent neural networks utilize training data for learning. They are characterized by "memory" because they obtain information from previous inputs through feedback loops 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.

[0368] Neural networks have feedback loops 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.

[0369] Even if the AI / ML model is well-trained and has a large amount of labeled data and concepts, after a period of time, due to many reasons, the performance of the model may decline when adding new unlabeled inputs. These reasons include, but are not limited to, concept drift, decline in recall accuracy due to deviation from true positives, and data drift over time. The feedback loop of the model can maintain the accuracy of AI results and ensure that the model maintains its performance and improvement, even when absorbing new unlabeled data. The feedback loop refers to the process of repeatedly using the predicted output of the AI model to train a new version of the model.

[0370] Initially, when training an AI / ML model, some labeled samples are used, which contain positive and negative examples of a concept (such as seat belt tightness) for the model to learn. Subsequently, unlabeled data is used to test the model. By using technologies such as deep learning and neural networks, the model can predict whether the desired concept (such as tightness, convenience score, score to be detected) exists in the unlabeled image. 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 will be 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 required in special cases. The feedback loop dynamically feeds the labeled data (automatically labeled or verified by the controller) back to the model and uses it as training data so that the system can dynamically improve its prediction in real time.

[0371] Figure 30B 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, meaning there is no teacher as 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 data that has already been predicted into the model. If the machine learning model has a feedback loop, the learning is further strengthened by rewarding each true positive output of the system. 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.

[0372] In one embodiment, the system further includes a network security module, which includes an information security management module that provides isolation between the communication module and the server.

[0373] 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 validating the security key, analyze whether there are potential network security threats 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.

[0374] 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 cybersecurity 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 cybersecurity threat is detected.

[0375] In one embodiment, the system may include a network security module.

[0376] 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 communicatively coupled to 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 cybersecurity threat in the first data message. If it is determined that the first data message does not contain a cybersecurity threat, the processor is further programmed to convert the first data message into a first data format associated with a vehicle environment and transmit the converted first data message to a vehicle system using a first communication protocol associated with the vehicle system.

[0377] 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 permission 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, using the security engine to perform asynchronous verification and encryption of data, including using a hardware-based module equipped with one or more security aspects for protecting the system to identify a user device (UD) containing credentials embodied in the hardware, where the security aspects include a hardware-based module for communicating with the user of the user device and the HSE.

[0378] In one embodiment, the system includes a network security module. The components of the network security module are described below. The data transmission between the system and the server through the communication module is first verified by the information security management module before being transmitted from the system to the server or from the server to the system. The information security management module can be used to analyze whether there is a potential cybersecurity threat in the data, encrypt the data when no cybersecurity threat is detected, and transmit the encrypted data to the system or the server.

[0379] In one embodiment, the network security module further includes an information security management module for providing isolation between the system and the server. The network security module protects data by performing the following technical steps. The information security management module is used to receive data from the communication module. The information security management module exchanges security keys when communication starts between the communication module and the server. The information security management module receives a security key from the server. The information security management module verifies the identity of the server by verifying the security key. The information security management module analyzes whether there are potential network security threats in the security key. The information security management module negotiates an encryption key between the communication module and the server. The information security management module receives encrypted data. When no network security threat is detected, the information security management module transmits the encrypted data to the server.

[0380] In one embodiment, the network security module protects data by performing the following technical steps. The information security management module is used to exchange security keys when communication starts between the communication module and the server. The information security management module receives a security key from the server. The information security management module verifies the identity of the server by verifying the security key. The information security management module analyzes whether there are potential network security threats in the security key. The information security management module negotiates an encryption key between the communication module and the server. The information security management module receives encrypted data. The information security management module decrypts the encrypted data and performs an integrity check on the decrypted data. When no network security threat is detected, the information security management module transmits the decrypted data to the communication module.

[0381] In one embodiment, the integrity check is a hash signature verification using the Secure Hash Algorithm 256 (SHA256) or a similar method. In one embodiment, the information security management module is configured to perform asynchronous authentication and verification on the communication between the communication module and the server. In one embodiment, the information security management module is configured to issue an alarm if a network security 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. 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.

[0382] In one embodiment, the server is physically isolated from the system through an information security management module. When the system communicates with the server, identity authentication is first performed on 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 identity authentication is passed. Similarly, the system and the server perform identity authentication on the information security management module. After the identity authentication is passed to the information security management module, the system and the server on both sides of the communication 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 identity authentication process, so the key needs to be bound to the session ID number; when the system sends data out, 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 after decryption, it verifies the integrity of the data. If the verification passes, the data is sent out through the communication module, otherwise the data is discarded. In one embodiment, the identity authentication is implemented using an asymmetric key with a signature.

[0383] In one embodiment, the signature is implemented through a pair of asymmetric keys trusted by the information security management module and the system, where the private key is used to sign the identities of both sides of the communication, and the public key is used to verify whether the identities of both sides of the communication are signed. The signed identity includes a pair of public key and private key. In other words, the signed identity refers to the common name of the certificate installed on the user machine. In one embodiment, both sides of the communication need to verify their identities through a pair of asymmetric keys, and a pair of unique asymmetric keys are used to identify the task of communicating with the information security management module of the system. In one embodiment, the dynamic key negotiation is encrypted using the RSA (Rivest-Shamir-Adleman) encryption algorithm. RSA is a public key cryptosystem widely used for secure data transmission. The negotiated keys include a data encryption key and a data integrity check key. In one embodiment, the data encryption method is the triple data encryption algorithm (3DES) encryption algorithm. The integrity check algorithm is the hash-based message authentication code (HMAC-MD5-128) algorithm. When outputting data, the integrity check calculation of the data is performed, and the calculated message authentication code (MAC) value is added to the header of the numerical data message, and then the data (including the MAC in the header) is encrypted using the 3DES algorithm. 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.

[0384] The information security management module ensures the security, reliability, and confidentiality of the communication between the system and the server through the identity authentication when both communication parties initiate data encryption and data integrity authentication. It is particularly suitable for embedded platforms with fewer 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 that the data on the server is not endangered by hacker attacks under Internet conditions.

[0385] 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 impossible to describe all conceivable combinations of components and / or computer-implemented methods. However, 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 "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 construed to be inclusive when used as a transitional word in the claims.

[0386] Without departing from the spirit or characteristics of the present invention, the present invention may also be embodied in other specific forms. The embodiments are illustrative rather than restrictive in all respects. Therefore, the appended claims rather than the description herein indicate the scope of the present invention. All changes within the meaning and scope equivalent to the claims are within its scope.

[0387] List of payments

[0388] Item 1. A system, comprising: a sensor module; and a control module, comprising: a processor; and a memory communicatively coupled to the processor, the memory including a sensor control module that, when executed by the processor, causes the processor to: determine a first state of charge of one or more batteries associated with a vehicle; determine whether the first state of charge is below a threshold state of charge level; determine one or more first geographical ranges including one or more first charging stations based on the first state of charge; determine one or more charge consumption factors affecting charge consumption in the one or more batteries; estimate charge consumption based on the one or more charge consumption factors; determine a second state of charge based on the charge consumption; determine one or more second geographical ranges including one or more second charging stations based on the second state of charge; and schedule one or more charging sessions with the one or more second charging stations to charge the one or more batteries.

[0389] 2. The system according to item 1, wherein the processor is operable to preset the threshold state of charge level.

[0390] Item 3. The system according to Item 1, wherein the first state of charge includes a measurement of a first amount of electrical energy available in the one or more batteries at a particular point in time.

[0391] Item 4. The system according to Item 3, wherein the first state of charge of the one or more batteries is expressed as a percentage.

[0392] Item 5. The system according to Item 1, wherein the one or more second geographical ranges cover a part of the one or more first geographical ranges.

[0393] Item 6. The system according to Item 1, wherein the one or more second geographical ranges are different from the one or more first geographical ranges.

[0394] Item 7. The system according to Item 1, wherein the one or more second geographical ranges completely overlap with the one or more first geographical ranges.

[0395] Item 8. The system according to Item 1, wherein the one or more charge consumption factors include one or more external charge consumption factors.

[0396] Item 9. The system according to Item 1, wherein the one or more charge consumption factors include one or more internal charge consumption factors.

[0397] Item 10. The system according to Item 8, wherein the one or more external charge consumption factors include at least one of environmental conditions, road surface conditions, distance between the one or more first charging stations and the vehicle, traffic conditions, waiting time, and driving mode.

[0398] Item 11. The system according to Item 10, wherein the environmental conditions include information on at least one of weather, climate, temperature, wind, storm, tornado, snow, sleet, and rain.

[0399] Item 12. The system according to Item 10, wherein the road surface conditions include information on at least one of road surface slipperiness, road surface friction, road surface inclination, road surface deviation, road surface smoothness, and road surface material.

[0400] Item 13. The system according to Item 10, wherein the traffic conditions include information on at least one of intersection area waiting time, traffic signal waiting time, travel time from the current position of the vehicle to the destination, one or more nearby vehicles, lanes, predefined driving speed, and obstacles.

[0401] Item 14. The system according to Item 10, wherein the driving mode includes information on at least one of the driver's driving profile, driving speed, and driving efficiency score.

[0402] Item 15. The system according to Item 1, wherein the second state of charge includes an estimate of the second amount of electricity in the one or more batteries taking into account the one or more charge consumption factors.

[0403] Item 16. The system according to Item 9, wherein the one or more internal charge consumption factors include at least one of vehicle weight, the state of health of the one or more batteries, occupant weight, luggage weight, vehicle specifications, vehicle operation mode, and vehicle fuel operation mode.

[0404] Item 17. The system according to Item 16, wherein the vehicle operation mode includes one of an autonomous driving mode, a non-autonomous mode, an autonomous mode, and a semi-autonomous mode.

[0405] Item 18. The system according to Item 16, wherein the vehicle fuel operation mode includes one of a hybrid mode, an electric mode, and a combustion fuel mode.

[0406] Item 19. The system according to Item 1, wherein the processor is operable to: use an artificial intelligence engine to determine a distance range that the vehicle can travel using the first state of charge; use an artificial intelligence engine to identify one or more first regions around the vehicle, the one or more first regions including the one or more first charging stations available for charging; use an artificial intelligence engine to determine the one or more first geographical ranges covering the one or more first regions; and use an artificial intelligence engine to provide a layout of the one or more first geographical ranges, in terms of determining one or more first geographical ranges including one or more first charging stations based on the first state of charge.

[0407] Item 20. The system according to Item 19, wherein the processor is operable to: determine the real-time position of the vehicle; determine one or more first charging stations around the real-time position of the vehicle; map the one or more first charging stations around the real-time position of the vehicle to one or more first regions; and mark the one or more first charging stations within the one or more first regions, in terms of using an artificial intelligence engine to identify the one or more first regions near the vehicle, the one or more first regions including the one or more first charging stations available for charging.

[0408] Item 21. The system according to Item 1, wherein the processor is operable, in determining one or more charge consumption factors affecting charge consumption in the one or more batteries, to: continuously sense, using the sensor module, one or more external charge consumption factors around the vehicle; determine at least one of a sudden change and an abnormal increase in vehicle charge consumption; associate at least one of the sudden change and the abnormal increase in charge consumption with the one or more external charge consumption factors; and learn, using the artificial intelligence engine, the one or more external charge consumption factors and charge consumption based on the association.

[0409] Item 22. The system according to Item 1, wherein the processor is operable, in determining one or more charge consumption factors affecting charge consumption in the one or more batteries, to: continuously sense, using the sensor module, one or more internal charge consumption factors; determine at least one of a sudden change and an abnormal increase in vehicle charge consumption; associate at least one of the sudden change and the abnormal increase in charge consumption with the one or more internal charge consumption factors; and learn, using the artificial intelligence engine, the one or more internal charge consumption factors and charge consumption based on the association.

[0410] Item 23. The system according to Item 1, wherein the processor is operable, in determining one or more charge consumption factors affecting charge consumption in the one or more batteries, to: continuously sense, using the sensor module, at least one of one or more events, one or more activities, and one or more actions; determine, using the artificial intelligence engine, one or more charge consumption factors causing at least one of the one or more events, the one or more activities, and the one or more actions; determine the charge consumption of at least one of the one or more events, the one or more activities, and the one or more actions; and learn, using the artificial intelligence engine, the one or more charge consumption factors and charge consumption.

[0411] Item 24. The system according to Item 23, wherein the one or more events include the vehicle traveling a predefined distance on an inclined surface.

[0412] Item 25. The system according to Item 24, wherein the processor uses the artificial intelligence engine to determine the surface inclination as one of the one or more charge consumption factors causing the one or more events.

[0413] Item 26. The system according to Item 23, wherein the one or more events include the vehicle traveling with a predefined load.

[0414] Item 27. The system according to Item 26, wherein the processor uses the artificial intelligence engine to determine the occupant weight as one of the one or more charge consumption factors causing the one or more events.

[0415] Item 28. The system according to Item 23, wherein the one or more events include a vehicle traveling in a traffic environment.

[0416] Item 29. The system according to Item 28, wherein the processor uses an artificial intelligence engine to determine a traffic condition as one or more charge consumption factors that cause the one or more events.

[0417] Item 30. The system according to Item 23, wherein the one or more events include a sudden discharge of the one or more batteries.

[0418] Item 31. The system according to Item 30, wherein the processor uses an artificial intelligence engine to determine the health state of the one or more batteries as one or more charge consumption factors that cause the one or more events.

[0419] Item 32. The system according to Item 1, wherein the sensor module includes at least one of one or more weight sensors, one or more load cells, 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 temperature sensors, one or more light sensors, one or more capacitive load cells, and one or more accelerometers.

[0420] Item 33. The system according to Item 1, wherein the processor, in terms of determining one or more second geographical ranges including one or more second charging stations based on a second state of charge, is operable to: use an artificial intelligence engine to determine a distance range that the vehicle can travel using the second state of charge; use an artificial intelligence engine to identify one or more second areas around the vehicle, the one or more second areas including one or more second charging stations available for charging; use an artificial intelligence engine to determine the one or more second geographical ranges covering the one or more second areas; and use an artificial intelligence engine to provide a layout of the one or more second geographical ranges.

[0421] Item 34. The system according to Item 33, wherein the processor, in terms of using an artificial intelligence engine to identify one or more second areas near the vehicle, the one or more second areas including one or more second charging stations available for charging, is operable to: determine the real-time position of the vehicle; determine one or more second charging stations around the real-time position of the vehicle; map the one or more second charging stations around the real-time position of the vehicle into one or more second areas; and mark the one or more second charging stations within the one or more second areas.

[0422] Clause 35. The system according to Clause 1, wherein the processor is operable to establish communication between the one or more second charging stations and the vehicle.

[0423] Clause 36. The system according to Clause 35, wherein the communication is wireless communication.

[0424] Clause 37. The system according to Clause 35, wherein the communication is wired communication.

[0425] Clause 38. The system according to Clause 1, wherein the processor's reserving the one or more second charging stations to charge the one or more batteries includes: determining the time when the vehicle arrives at the location of the one or more second charging stations; determining the charging duration for the one or more batteries to complete charging; determining the remaining time for the vehicle based on a trip associated with the vehicle user; using an artificial intelligence engine to calculate one or more charging sessions based on at least one of the arrival time, the charging duration, and the remaining time; and compiling one or more messages to be sent to the one or more second charging stations based on the one or more charging sessions.

[0426] Clause 39. The system according to Clause 38, wherein the one or more messages include information on vehicle identification, vehicle location, distance between the vehicle and the charging station, charging sequence, charging date, second state of charge, charging session start time, charging session end time, predetermined time period, and charging duration.

[0427] Clause 40. The system according to Clause 38, wherein the processor is operable to enable an autonomous mode in the vehicle based on one or more charging sessions.

[0428] Clause 41. The system according to Clause 40, wherein the processor transmits instructions to an electric drive unit to autonomously maneuver the vehicle to the one or more second charging stations before a predetermined time period.

[0429] Clause 42. A method includes: determining a first state of charge of one or more batteries associated with a vehicle; determining whether the first state of charge is below a threshold state of charge level; determining one or more first geographical ranges including one or more first charging stations based on the first state of charge; determining one or more charge consumption factors affecting charge consumption in the one or more batteries; estimating charge consumption based on the one or more charge consumption factors; determining a second state of charge based on the charge consumption; determining one or more second geographical ranges including one or more second charging stations based on the second state of charge; and reserving one or more charging sessions with the one or more second charging stations to charge the one or more batteries.

[0430] Item 43. The method according to Item 42, wherein determining one or more first geographical ranges including one or more first charging stations based on the first state of charge includes: using an artificial intelligence engine to determine the distance range that the vehicle can travel using the first state of charge; using an artificial intelligence engine to identify one or more first areas around the vehicle, the one or more first areas including one or more first charging stations available for charging; using an artificial intelligence engine to determine the one or more first geographical ranges covering the one or more first areas; and using an artificial intelligence engine to provide the layout of the one or more first geographical ranges.

[0431] Item 44. The method according to Item 43, wherein using an artificial intelligence engine to identify one or more first areas near the vehicle, the one or more first areas including the one or more first charging stations available for charging, includes: determining the real-time position of the vehicle; determining one or more first charging stations around the real-time position of the vehicle; mapping the one or more first charging stations around the real-time position of the vehicle into one or more first areas; and marking the one or more first charging stations within the one or more first areas.

[0432] Item 45. The method according to Item 42, wherein determining one or more charge consumption factors affecting the charge consumption in the one or more batteries includes: using a sensor module to continuously sense one or more external charge consumption factors around the vehicle; determining at least one of a sudden change and an abnormal increase in the vehicle charge consumption; associating at least one of the sudden change and the abnormal increase in the charge consumption with the one or more external charge consumption factors; and using an artificial intelligence engine to learn the one or more external charge consumption factors and the charge consumption based on the association.

[0433] Item 46. The method according to Item 42, wherein determining one or more charge consumption factors affecting the charge consumption in the one or more batteries includes: using a sensor module to continuously sense one or more internal charge consumption factors; determining at least one of a sudden change and an abnormal increase in the vehicle charge consumption; associating at least one of the sudden change and the abnormal increase in the charge consumption with the one or more internal charge consumption factors; and using an artificial intelligence engine to learn the one or more internal charge consumption factors and the charge consumption based on the association.

[0434] Item 47. The method according to Item 42, wherein determining one or more charge consumption factors affecting charge consumption in the one or more batteries includes: continuously sensing, using a sensor module, at least one of one or more events, one or more activities, and one or more actions; determining, using an artificial intelligence engine, one or more charge consumption factors that cause at least one of the one or more events, the one or more activities, and the one or more actions; determining the charge consumption of at least one of the one or more events, the one or more activities, and the one or more actions; and learning, using an artificial intelligence engine, one or more charge consumption factors and charge consumption.

[0435] Item 48. The method according to Item 42, wherein determining the one or more second geographical ranges including the one or more second charging stations based on a second state of charge includes: determining, using an artificial intelligence engine, a distance range that the vehicle can travel using the second state of charge; identifying, using an artificial intelligence engine, one or more second regions around the vehicle, the one or more second regions including one or more second charging stations available for charging; determining, using an artificial intelligence engine, the one or more second geographical ranges covering the one or more second regions; and providing, using an artificial intelligence engine, a layout of the one or more second geographical ranges.

[0436] Item 49. The method according to Item 48, wherein identifying, using an artificial intelligence engine, one or more second regions near the vehicle, the one or more second regions including one or more second charging stations available for charging, includes: determining the real-time position of the vehicle; determining one or more second charging stations around the real-time position of the vehicle; mapping the one or more second charging stations around the real-time position of the vehicle into the one or more second regions; and marking the one or more second charging stations within the one or more second regions.

[0437] Item 50. The method according to Item 42, further comprising: establishing communication between the one or more second charging stations and the vehicle.

[0438] Item 51. The method according to Item 42, wherein reserving the one or more second charging stations to charge the one or more batteries includes: determining the time when the vehicle arrives at the location where the one or more second charging stations are located; determining the charging duration for the one or more batteries to complete charging; determining the remaining time for the vehicle based on a trip associated with the vehicle user; calculating, using an artificial intelligence engine, one or more charging sessions based on at least one of the arrival time, the charging duration, and the remaining time; and compiling, based on the one or more charging sessions, one or more messages to be sent to the one or more second charging stations.

[0439] Item 52. A non-transitory computer-readable storage medium comprising a series of instructions which, when executed by a processor, cause: determining a first state of charge of one or more batteries associated with a vehicle; determining whether the first state of charge is below a threshold state of charge level; determining one or more first geographical ranges including one or more first charging stations based on the first state of charge; determining one or more charge consumption factors affecting charge consumption in the one or more batteries; estimating charge consumption based on the one or more charge consumption factors; determining a second state of charge based on the charge consumption; determining one or more second geographical ranges including one or more second charging stations based on the second state of charge; and scheduling one or more charging sessions with the one or more second charging stations to charge the one or more batteries.

[0440] Item 53. The non-transitory computer-readable storage medium according to Item 52, wherein determining one or more first geographical ranges including one or more first charging stations based on the first state of charge causes: using an artificial intelligence engine to determine a range of distances that the vehicle can travel using the first state of charge; using an artificial intelligence engine to identify one or more first areas around the vehicle, the one or more first areas including the one or more first charging stations available for charging; using an artificial intelligence engine to determine one or more first geographical ranges covering the one or more first areas; and using an artificial intelligence engine to provide a layout of the one or more first geographical ranges.

[0441] Item 54. The non-transitory computer-readable storage medium according to Item 53, wherein using an artificial intelligence engine to identify one or more first areas near the vehicle (including the one or more first charging stations available for charging) is caused by the following steps: determining the real-time position of the vehicle; determining one or more first charging stations around the real-time position of the vehicle; mapping the one or more first charging stations around the real-time position of the vehicle into one or more first areas; and marking the one or more first charging stations within the one or more first areas.

[0442] Item 55. The non-transitory computer-readable storage medium according to Item 52, wherein determining one or more charge consumption factors affecting charge consumption in the one or more batteries is caused by the following steps: using a sensor module to continuously sense one or more external charge consumption factors around the vehicle; determining at least one of a sudden change and an abnormal increase in the charge consumption of the vehicle; associating at least one of the sudden change and the abnormal increase in the charge consumption with the one or more external charge consumption factors; and using an artificial intelligence engine to learn the one or more external charge consumption factors and charge consumption based on the association.

[0443] Item 56. The non-transitory computer-readable storage medium according to Item 52, wherein determining one or more charge consumption factors that affect charge consumption in the one or more batteries is caused by the following steps: continuously sensing, using a sensor module, one or more internal charge consumption factors; determining at least one of a sudden change and an abnormal increase in the charge consumption of the vehicle; associating at least one of the sudden change and the abnormal increase in the charge consumption with the one or more internal charge consumption factors; and using an artificial intelligence engine to learn the one or more internal charge consumption factors and the charge consumption based on the association.

[0444] Item 57. The non-transitory computer-readable storage medium according to Item 52, wherein determining one or more charge consumption factors that affect charge consumption in the one or more batteries is caused by the following steps: continuously sensing, using a sensor module, at least one of one or more events, one or more activities, and one or more actions; using an artificial intelligence engine to determine one or more charge consumption factors that cause at least one of the one or more events, the one or more activities, and the one or more actions; determining the charge consumption of at least one of the one or more events, the one or more activities, and the one or more actions; and using an artificial intelligence engine to learn the one or more charge consumption factors and the charge consumption.

[0445] Item 58. The non-transitory computer-readable storage medium according to Item 58, wherein determining one or more second geographical ranges including one or more second charging stations based on a second state of charge includes: using an artificial intelligence engine to determine a distance range that the vehicle can travel using the second state of charge; using an artificial intelligence engine to identify one or more second regions around the vehicle, the one or more second regions including one or more second charging stations available for charging; using an artificial intelligence engine to determine the one or more second geographical ranges covering the one or more second regions; and using an artificial intelligence engine to provide a layout of the one or more second geographical ranges.

[0446] Item 59. The non-transitory computer-readable storage medium according to Item 58, wherein using an artificial intelligence engine to identify one or more second regions near the vehicle, the one or more second regions including one or more second charging stations available for charging, causes the processor to: determine the real-time position of the vehicle; determine one or more second charging stations around the real-time position of the vehicle; map the one or more second charging stations around the real-time position of the vehicle into one or more second regions; and mark the one or more second charging stations within the one or more second regions.

[0447] Item 60. The non-transitory computer-readable storage medium according to Item 52, further comprising: establishing communication between the one or more second charging stations and the vehicle.

[0448] Item 61. The non-transitory computer-readable storage medium according to Item 52, wherein reserving the one or more second charging stations to charge the one or more batteries includes: determining the time when the vehicle arrives at the location where the one or more second charging stations are located; determining the charging duration for the one or more batteries to complete charging; determining the remaining time for the vehicle based on a trip associated with the vehicle user; using an artificial intelligence engine to calculate one or more charging sessions based on at least one of the arrival time, the charging duration, and the remaining time; and compiling one or more messages sent to the one or more second charging stations based on the one or more charging sessions.

Claims

1. A system comprising: Sensor module; as well as Control module, including: Processor; and A memory communicatively coupled to the processor, the memory including a sensor control module, which, when executed by the processor, causes the processor to: determining a first state of charge of one or more batteries associated with the vehicle; determining whether the first state of charge is below a threshold charge level; determining one or more first geographic ranges including one or more first charging stations based on the first state of charge; determining one or more charge depletion factors that affect charge depletion in the one or more batteries; estimating charge depletion based on the one or more charge depletion factors; determining a second state of charge based on the charge depletion; determining one or more second geographic ranges including one or more second charging stations based on the second state of charge; and One or more charging sessions are scheduled with the one or more second charging stations to charge the one or more batteries.

2. The system according to claim 1, wherein: In determining one or more first geographic ranges including one or more first charging stations based on the first state of charge, the processor may be operable to: Determine, using an artificial intelligence engine, a range of distances that the vehicle can travel using the first state of charge; identifying, using an artificial intelligence engine, one or more first areas around the vehicle, the one or more first areas including the one or more first charging stations available for charging; determining, using an artificial intelligence engine, the one or more first geographic ranges encompassing the one or more first areas; as well as An artificial intelligence engine is used to provide a layout of the one or more first geographic ranges.

3. The system according to claim 2, wherein: In terms of using the artificial intelligence engine to identify one or more first areas in the vicinity of the vehicle, the one or more first areas including the one or more first charging stations available for charging, the processor is operable to: Determine the real-time location of the vehicle; determining the one or more first charging stations around a real-time location of the vehicle; mapping the one or more first charging stations around the real-time location of the vehicle to the one or more first areas; as well as The one or more first charging stations within the one or more first areas are marked.

4. The system according to claim 2, wherein: In determining one or more charge depletion factors affecting charge depletion in the one or more batteries, the processor may be operable to: continuously sensing at least one of one or more events, one or more activities, and one or more actions using a sensor module; determining, using an artificial intelligence engine, one or more charge depletion factors that led to at least one of the one or more events, the one or more activities, and the one or more actions; determining a charge consumption of at least one of the one or more events, the one or more activities, and the one or more actions; as well as The one or more charge consumption factors and charge consumption are learned using an artificial intelligence engine.

5. The system according to claim 4, wherein: The one or more events include the vehicle traveling a predefined distance on an inclined surface.

6. The system according to claim 5, wherein: The processor uses an artificial intelligence engine to determine surface slope as the one or more charge depletion factors that caused the one or more events.

7. The system according to claim 4, wherein: The one or more events include the vehicle being driven with a predefined load.

8. The system according to claim 7, wherein: The processor uses an artificial intelligence engine to determine occupant weight as the one or more charge depleting factors that caused the one or more events.

9. The system according to claim 4, wherein: The one or more events include a sudden discharge of the one or more batteries.

10. The system according to claim 9, wherein: The processor determines a state of health of one or more batteries using an artificial intelligence engine as one or more charge depletion factors leading to the one or more events.

11. The system according to claim 2, wherein: The sensor module includes at least one of one or more weight sensors, one or more weighing sensors, 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 temperature sensors, one or more light sensors, one or more capacitive weighing sensors and one or more accelerometers.

12. The system according to claim 2, wherein: The processor is operable to enable an autonomous mode in the vehicle based on the one or more charging sessions.

13. A method comprising: determining a first state of charge of one or more batteries associated with the vehicle; determining whether the first state of charge is below a threshold charge level; determining one or more first geographic ranges including one or more first charging stations based on the first state of charge; determining one or more charge depletion factors that affect charge depletion in the one or more batteries; estimating charge depletion based on the one or more charge depletion factors; determining a second state of charge based on the charge consumption; determining one or more second geographic ranges including one or more second charging stations based on the second state of charge; as well as One or more charging sessions are scheduled with the one or more second charging stations to charge the one or more batteries.

14. The method according to claim 13, wherein: Determining one or more first geographic ranges including one or more first charging stations based on the first state of charge includes: Determine, using an artificial intelligence engine, a range of distances that the vehicle can travel using the first state of charge; identifying, using an artificial intelligence engine, one or more first areas around the vehicle, the one or more first areas including the one or more first charging stations available for charging; determining, using an artificial intelligence engine, the one or more first geographic ranges encompassing the one or more first areas; and An artificial intelligence engine is used to provide a layout of the one or more first geographic ranges.

15. The method according to claim 14, wherein: Identifying, using an artificial intelligence engine, one or more first areas near the vehicle, the one or more first areas including the one or more first charging stations available for charging, comprising: Determine the real-time location of the vehicle; determining the one or more first charging stations around a real-time location of the vehicle; mapping the one or more first charging stations around the real-time location of the vehicle into the one or more first areas; and The one or more first charging stations within the one or more first areas are marked.

16. The method according to claim 13, wherein: Determining one or more charge depletion factors that affect charge depletion in the one or more batteries includes: continuously sensing one or more external charge depletion factors around the vehicle using a sensor module; determining at least one of a sudden change and an abnormal increase in charge consumption of the vehicle; associating at least one of a sudden change and an abnormal increase in charge depletion with the one or more external charge depletion factors; and The one or more external charge depletion factors and the charge depletion are learned based on the association using an artificial intelligence engine.

17. The method according to claim 13, wherein: Determining one or more charge depletion factors that affect charge depletion in the one or more batteries includes: continuously sensing the one or more internal charge depletion factors using a sensor module; determining at least one of a sudden change and an abnormal increase in charge consumption of the vehicle; associating at least one of a sudden change and an abnormal increase in charge depletion with the one or more internal charge depletion factors; and The one or more internal charge consumption factors and the charge consumption are learned based on the association using an artificial intelligence engine.

18. A non-transitory computer readable storage medium comprising a series of instructions which, when executed by a processor, cause: determining a first state of charge of one or more batteries associated with the vehicle; determining whether the first state of charge is below a threshold charge level; determining one or more first geographic ranges including one or more first charging stations based on the first state of charge; determining one or more charge depletion factors that affect charge depletion in the one or more batteries; estimating charge depletion based on the one or more charge depletion factors; determining a second state of charge based on the charge consumption; determining one or more second geographic ranges including one or more second charging stations based on the second state of charge; as well as One or more charging sessions are scheduled with the one or more second charging stations to charge the one or more batteries.

19. The non-transitory computer-readable storage medium of claim 18, wherein: Determining one or more second geographic ranges including one or more second charging stations based on the second state of charge includes: Determine, using an artificial intelligence engine, a range of distances that the vehicle can travel using the second state of charge; identifying, using the artificial intelligence engine, one or more second areas around the vehicle, the one or more second areas including one or more second charging stations available for charging; determining, using an artificial intelligence engine, the one or more second geographic ranges encompassing the one or more second regions; and An artificial intelligence engine is used to provide a layout of the one or more second geographic ranges.

20. The non-transitory computer-readable storage medium of claim 18, wherein: Reserving the one or more second charging stations to charge the one or more batteries includes: determining a time at which the vehicle arrives at the location of the one or more second charging stations; determining a charging duration for one or more batteries to complete charging; determining a remaining time for the vehicle based on a trip associated with a vehicle user; calculating, using an artificial intelligence engine, the one or more charging sessions based on at least one of an arrival time, a charging duration, and a remaining time; and One or more messages are compiled based on the one or more charging sessions and sent to the one or more second charging stations.

Images