System

Abstract

A system is provided.SOLUTION: A system comprising: means for measuring temperature, voltage, current, and remaining energy of a battery in a vehicle; means for periodically transmitting measurement data of the battery; means for receiving the measurement data of the battery and performing energy usage optimization; means for transmitting a command to an energy management system of the vehicle based on the energy usage optimization; and means for adjusting a state of the battery based on the command.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The technology of the present disclosure relates to a system. [Background technology]

[0002] Patent document 1 discloses a persona chatbot control method performed by at least one processor, the method including the steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to a description of the chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2022-180282 Summary of the Invention [Problem to be solved by the invention]

[0004] Conventional vehicle battery systems have difficulty balancing energy efficiency and sustainability. They lack real-time monitoring of battery status and optimal energy management, resulting in the inability to maximize battery life and vehicle range. Furthermore, they lack an interface that allows users to easily adjust energy management settings. To address these issues, a more efficient and sustainable vehicle battery system is needed. [Means for solving the problem]

[0005] To solve this problem, the present invention provides the following means. First, a means for measuring the temperature, voltage, current, and remaining energy of the battery in the vehicle is provided. A means for periodically transmitting this measurement data to a server is provided, and the server optimizes energy use based on the received data. Energy use optimization is achieved by simulating multiple scenarios and selecting the optimal energy management method. The server then sends commands to the vehicle's energy management system based on the optimization results, and adjusts the battery status based on those commands. The present invention also provides a user application that allows users to monitor and check the battery status in real time. Furthermore, a means for users to adjust energy management settings through the application is provided. This achieves both energy efficiency and sustainability, extending battery life and maximizing the vehicle's driving range.

[0006] A "battery" is a device that provides power by storing and distributing electricity.

[0007] A "battery cell" is one of the components of a battery, and is a unit that individually stores electricity and charges and discharges it.

[0008] "Vehicle" means a means of transportation powered by a battery, including electric vehicles and hybrid vehicles.

[0009] A "sensor" is a device that detects a physical quantity (temperature, voltage, current, etc.) and converts it into an electrical signal.

[0010] A "server" is a high performance computer system for providing services such as trading, data management, and computation.

[0011] An "energy management system" is a system that optimizes the energy usage of a vehicle's battery and other power-consuming devices.

[0012] "Real-time" refers to a state in which data is processed immediately the moment it is generated, resulting in high responsiveness.

[0013] "User" refers to the person utilizing the system to monitor and control the status of the battery.

[0014] An "application" is software that allows a user to operate on a digital device.

[0015] "Simulation" is a method of simulating real-world systems and processes and analyzing and evaluating their behavior.

[0016] "Command" refers to an operational command sent from the server to the vehicle's energy management system.

[0017] "Optimization" is the process of optimizing resources and conditions to achieve a specific goal. [Brief explanation of the drawings]

[0018] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8]FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0019] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0020] First, the terms used in the following description will be explained.

[0021] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0022] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0023] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0024] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0025] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0026] [First embodiment]

[0027] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0028] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0029] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0030] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0031] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0032] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0033] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0034] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0035] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0036] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0037] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0038] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0039] The present invention relates to battery systems in vehicles, and in particular to a system for improving energy efficiency and sustainability, which includes technology for monitoring the battery's condition in real time and achieving optimal energy usage.

[0040] Server Processing

[0041] The server is the heart of the present invention and performs the following processes.

[0042] 1. Receives battery measurement data (temperature, voltage, current, remaining charge) sent from the vehicle.

[0043] 2. The received measurement data is analyzed and an energy usage optimization algorithm is run, which simulates multiple scenarios, evaluates the results, and selects the optimal energy management method.

[0044] 3. Based on this selection, specific instructions are generated and sent to the vehicle's energy management system, such as load balancing, charging / discharging timing, and cooling system adjustments.

[0045] Terminal (vehicle side) processing

[0046] The terminal is installed in the vehicle and performs the following processing.

[0047] 1. Measure the battery status (temperature, voltage, current, remaining capacity) through sensors and send the data to the server at regular intervals.

[0048] 2. Receive and analyze commands sent from the server, such as "reduce energy consumption for the next hour" or "start fast charging."

[0049] 3. Based on the received commands, the system performs tasks such as charging and discharging the battery, operating the cooling system, and optimizing energy consumption in real time.

[0050] User Action

[0051] The user performs the following operations through a dedicated application.

[0052] 1. Launch the application and monitor your vehicle's battery status in real time.

[0053] 2. You can check your energy usage history through the application, such as daily energy consumption and charging / discharging schedules.

[0054] 3. Energy management settings can be adjusted through the application, such as "enable eco mode" or "delay the next charging session," allowing users to customize energy management to suit their lifestyle.

[0055] Specific examples

[0056] For example, consider the case where a vehicle's battery temperature rises on a hot day.

[0057] Terminal (vehicle side) processing: The vehicle's sensor detects a rise in battery temperature and sends that data (e.g., 45°C) to the server.

[0058] Server processing: The server receives this data and uses an algorithm to calculate the optimal course of action, resulting in a command to "activate the cooling system to lower the battery temperature."

[0059] Terminal processing: Based on the received command, the vehicle's energy management system activates the cooling system to maintain the battery temperature within an appropriate range.

[0060] User Action: The user can view this information in real time in the application. For example, the user can see that the battery temperature has dropped from 45°C to 25°C.

[0061] Through this process, the system of the present invention significantly improves battery efficiency and sustainability, extending vehicle range and battery life.

[0062] The processing flow will be explained below.

[0063] Server Processing

[0064] Step 1:

[0065] The server waits for battery measurement data to be sent from the vehicle.

[0066] Step 2:

[0067] The server receives battery measurement data sent from the vehicle, including temperature, voltage, current, and remaining energy.

[0068] Step 3:

[0069] The server analyzes the received measurement data, which includes outlier detection and data normalization.

[0070] Step 4:

[0071] The server runs an energy usage optimization algorithm based on the analyzed data, simulating multiple scenarios and evaluating the results.

[0072] Step 5:

[0073] The server selects the optimal energy management strategy and generates specific instructions based on it, including load balancing, charging and discharging timing, and cooling system adjustments.

[0074] Step 6:

[0075] The server transmits the generated command to the vehicle (terminal).

[0076] Terminal (vehicle side) processing

[0077] Step 1:

[0078] The device activates sensors to measure the battery's temperature, voltage, current, and remaining energy.

[0079] Step 2:

[0080] The terminal collects the measurement data from the sensors and assembles them into a single data packet.

[0081] Step 3:

[0082] The terminal transmits the measurement data to the server at regular intervals.

[0083] Step 4:

[0084] The terminal waits for a command sent from the server.

[0085] Step 5:

[0086] The terminal analyzes the command received from the server, including checking the type of command and how to execute it.

[0087] Step 6:

[0088] Based on the received instructions, the device charges and discharges the battery, activates the cooling system, and optimizes energy consumption.

[0089] User Action

[0090] Step 1:

[0091] The user starts a dedicated application.

[0092] Step 2:

[0093] The user requests data from the server to check the current battery status from the application.

[0094] Step 3:

[0095] The user monitors the battery status displayed in the application in real time.

[0096] Step 4:

[0097] Through the application, users can check their energy usage history, including energy consumption and charging / discharging schedules.

[0098] Step 5:

[0099] The user changes the energy management settings through the application.

[0100] Step 6:

[0101] Any changes to the user's settings are sent to the server, which then readjusts the energy management algorithms based on the settings.

[0102] This allows users to monitor battery status in real time and adjust energy management settings to suit their lifestyle.

[0103] Example 1

[0104] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0105] The aim of this invention is to improve the energy efficiency and sustainability of in-vehicle battery systems. However, conventional systems do not adequately monitor battery status in real time and perform data analysis and optimization algorithms to optimize energy usage. As a result, efficient battery use and extended battery life have been challenges.

[0106] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0107] In this invention, the server includes means for receiving measurement data and storing it in a database, means for analyzing the stored measurement data, and means for executing an energy usage optimization algorithm based on the analysis results, thereby enabling real-time monitoring of the battery status, selecting an optimal energy management method, and generating and transmitting commands, thereby enabling efficient use of the battery and extending its lifespan.

[0108] A "vehicle" is a machine that has a battery inside and moves by consuming energy.

[0109] A "battery" is a device that converts chemical energy into electrical energy and provides power for a period of time.

[0110] "Measurement data" is numerical data that indicates information about the state of the battery, and specifically includes temperature, voltage, current, and remaining energy.

[0111] A "server" is a computer system that receives, stores, analyzes, and processes data as needed.

[0112] A "database" is an information system for efficiently storing and managing large amounts of data.

[0113] "Analysis" is the act of evaluating and understanding the state and characteristics of an object based on collected data.

[0114] An "optimization algorithm" is a computational procedure for maximizing or minimizing the performance of a goal while taking into account multiple criteria.

[0115] A "command" is a specific operation instruction sent from the server to the terminal.

[0116] An "energy management system" is a system for managing and optimizing the energy consumption of batteries and vehicles.

[0117] "Real-time" refers to the immediate reflection of current status and behavior.

[0118] The present invention relates to a battery system in a vehicle, and in particular to a system for improving energy efficiency and sustainability, including technology for monitoring the state of the vehicle battery in real time to achieve optimal energy usage.

[0119] Server Processing

[0120] The server is the heart of the invention, receiving battery measurement data (temperature, voltage, current, remaining charge) sent from the vehicle and storing it in a database. The server uses MySQL or PostgreSQL as its database management system (DBMS). The stored data is analyzed and an energy usage optimization algorithm is executed. This algorithm simulates multiple scenarios and evaluates the results to select the optimal energy management method. Analysis tools such as Python's Pandas and NumPy are used for the analysis. Based on the results, specific commands (e.g., load balancing, charging / discharging timing, and cooling system adjustment) are generated and sent to the vehicle's energy management system.

[0121] Terminal (vehicle side) processing

[0122] The terminal is installed inside the vehicle and measures the battery condition through sensors, periodically sending the data to the server. A communications library is used to send the data. The terminal also receives and analyzes commands sent from the server. This analysis includes parsing the data and judging various conditions. Based on the received commands, the terminal performs real-time operations such as charging and discharging the battery, operating the cooling system, and optimizing energy consumption.

[0123] User Action

[0124] Users can monitor their vehicle's battery status in real time through a dedicated application. This application runs on a mobile device and provides the vehicle's battery status. Users can also check their past energy usage history through the application. Specifically, this includes functions to display daily energy consumption and charging / discharging schedules. In addition, they can adjust energy management settings. For example, they can enable Eco Mode or delay the next charging session.

[0125] Specific examples

[0126] For example, consider the case where a vehicle's battery temperature rises on a hot day. The device's sensor detects the rise in battery temperature and sends that data (for example, 45°C) to the server. The server receives this data, uses an algorithm to calculate the optimal response, and generates a command to "activate the cooling system to lower the battery temperature." Based on the received command, the vehicle's energy management system activates the cooling system to maintain the battery temperature within an appropriate range. The user can check this information in real time in the application. For example, they can see that the battery temperature has dropped from 45°C to 25°C.

[0127] Prompt Sentence Examples

[0128] Example prompts to input to a generative AI model:

[0129] Please write a description of the functionality of a vehicle's battery management system, including how sensors measure battery status and send that data to a server for analysis and optimization. Also, please include functionality that allows users to monitor battery status and adjust energy management through an application.

[0130] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0131] Step 1:

[0132] Server data reception

[0133] Input: Battery measurement data sent from the vehicle (temperature, voltage, current, remaining energy)

[0134] Processing: The server receives this data via HTTP communication. Specifically, the communication module parses and validates the received data.

[0135] Output: Measurement data in a format suitable for analysis

[0136] Step 2:

[0137] Server database storage

[0138] Input: Measurement data in a format suitable for analysis

[0139] Processing: The server stores the received data in a database and executes SQL queries using MySQL or PostgreSQL as the database management system (DBMS).

[0140] Output: Measurement data stored in a database

[0141] Step 3:

[0142] Server data analysis

[0143] Input: Measurement data stored in the database

[0144] Processing: The server uses Python's Pandas and NumPy to analyze the stored data, including calculating the mean, standard deviation, and outlier detection.

[0145] Output: Parsed battery data

[0146] Step 4:

[0147] Optimization algorithm execution on the server

[0148] Input: Parsed battery data

[0149] Processing: The server runs an energy usage optimization algorithm based on the analysis results. This algorithm uses Gurobi and SciPy to simulate multiple scenarios and select the optimal energy management method.

[0150] Output: Optimized energy management methods and specific directives

[0151] Step 5:

[0152] Server command generation and transmission

[0153] Input: Optimized energy management methods and specific directives

[0154] Processing: The server formats the command in JSON format and sends it to the vehicle's terminal via HTTP communication.

[0155] Output: Commands sent to the vehicle's terminal

[0156] Step 6:

[0157] Device sensor data measurement

[0158] Input: None

[0159] Processing: The terminal measures the battery status (temperature, voltage, current, remaining energy) using sensors in the vehicle, including temperature, voltage, and current sensors.

[0160] Output: Measured battery data

[0161] Step 7:

[0162] Data transmission from the device

[0163] Input: Measured battery data

[0164] Processing: The device sends the data to the server by performing an HTTP POST request using a communication library.

[0165] Output: Battery data sent to the server

[0166] Step 8:

[0167] Terminal command reception and analysis

[0168] Input: Command sent from the server

[0169] Processing: The device receives the command, analyzes the command content, parses the JSON format data, and makes a decision based on various conditions.

[0170] Output: Parsed command content

[0171] Step 9:

[0172] Terminal command execution

[0173] Input: Parsed command content

[0174] Processing: Based on the received instructions, the device will charge and discharge the battery, activate the cooling system, and optimize energy consumption in real time, such as activating the cooling system and adjusting the charging schedule.

[0175] Output: Energy management operations performed

[0176] Step 10:

[0177] Real-time user monitoring

[0178] Input: Battery data

[0179] Processing: The user launches a dedicated application, which retrieves the latest battery data from the server and displays it.

[0180] Output: Real-time updated battery status

[0181] Step 11:

[0182] Check user's past data

[0183] Input: Battery usage history for a user-specified period

[0184] Processing: The application retrieves historical data from the server and displays it to the user in the form of graphs and lists.

[0185] Output: Display of past energy usage history

[0186] Step 12:

[0187] Adjusting User Settings

[0188] Input: Energy management settings changed by the user

[0189] Processing: The user adjusts the energy management settings through the application's settings screen and sends the settings to the server.

[0190] Output: Updated Energy Management Settings

[0191] (Application example 1)

[0192] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0193] Conventional vehicle battery systems lack the technology to monitor battery status in real time and perform optimal energy management. They also lack sufficient means to provide users with timely energy management information, such as notifications of abnormal values ​​or displaying past usage history. Another issue is that it is difficult for users to adjust energy management settings via smart devices.

[0194] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0195] In this invention, the server includes a means for receiving battery measurement data and optimizing energy use, a means for sending commands to the vehicle's energy management system based on the energy use optimization, a means for displaying battery measurement data on the smart device in real time, a means for notifying of abnormal values, a means for presenting the battery energy management status as alerts or commands via the smart device, and a means for retrieving and displaying past battery usage history from a database. This enables optimal energy management by monitoring the battery status in real time and immediately notifying the user if an abnormality occurs. Furthermore, the user can easily check past usage history and adjust energy management settings via the smart device.

[0196] "Battery temperature" refers to the degree of thermal energy currently held by the battery in the vehicle.

[0197] "Voltage" refers to the potential difference produced by a vehicle's battery.

[0198] "Current" is a quantity that indicates the flow of electrons from a battery in a vehicle.

[0199] "Remaining energy" is the total amount of energy currently remaining in the vehicle's battery.

[0200] "Measurement data" refers to information about the battery's temperature, voltage, current, and remaining energy.

[0201] The "transmission means" is a communication means for sending the measurement data to the server.

[0202] The "optimization means" is a means for executing an algorithm to improve the efficiency of energy use based on the measurement data.

[0203] A "command" is an operational instruction sent to the energy management system.

[0204] A "smart device" is a multi-function device that has the ability to connect to the Internet and run applications.

[0205] The "real-time display means" is a means for displaying battery measurement data on a smart device in real time.

[0206] The "abnormal value notification means" is a means for notifying when an abnormality in the battery state is detected.

[0207] The "energy management status presentation means" is a means for presenting the optimization status of energy usage to the user as alerts or instructions via a smart device.

[0208] "Past usage history" refers to data on the battery's past voltage, current, temperature, and remaining energy.

[0209] A "database" is an information storage means for recording and saving past usage history.

[0210] This invention relates to a battery system for autonomous vehicles, and in particular to a system for improving energy efficiency and sustainability. The system measures the temperature, voltage, current, and remaining energy of the vehicle battery in real time, enabling optimal energy management.

[0211] Server Processing

[0212] The server is the core of the present invention and performs the following processes: First, it receives battery measurement data (temperature, voltage, current, remaining charge) sent from the vehicle. It analyzes this data and runs an energy usage optimization algorithm. The hardware and software used include cloud servers (e.g., AWS Lambda, Google Cloud Functions). The algorithm simulates multiple scenarios, evaluates the results, and selects the optimal energy management method. Finally, it generates and sends commands to the vehicle's energy management system based on the optimization results.

[0213] Terminal (vehicle side) processing

[0214] The terminal is installed inside the vehicle and measures the battery's status (temperature, voltage, current, remaining charge) through sensors, sending the data to a server at regular intervals. This data is displayed in real time mainly through smart devices. It also receives commands sent from the server and, based on those commands, performs tasks such as charging and discharging the battery, operating the cooling system, and optimizing energy consumption. The hardware used consists of a sensor system and communication module inside the vehicle.

[0215] User Action

[0216] Users use a dedicated smart device (e.g., smart glasses or a smartphone) to perform the following processes. First, the smart device has a function to display battery measurement data in real time. If an abnormal value is detected, an alert will be sent. In addition, past battery usage history can be retrieved from a database and easily checked through the smart device. Furthermore, users can adjust energy management settings through the smart device, which allows energy management to be optimized to suit their individual usage conditions.

[0217] Specific examples

[0218] If the battery temperature rises on a hot day, the following process occurs: The device's sensor detects a rise in battery temperature (e.g., 50°C) and sends the data to the server. The server receives this data and generates a command to activate the cooling system. This command activates the vehicle's cooling system, maintaining the battery temperature within an appropriate range (e.g., 25°C to 45°C). The user can check the change in battery temperature in real time through the smart glasses. Furthermore, if an abnormal value is detected, a prompt message will be displayed: "The current battery temperature is 50°C. Please activate the cooling system."

[0219] This allows the system of the present invention to significantly improve battery efficiency and sustainability, extending vehicle range and battery life.

[0220] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0221] Specific explanation of processing steps

[0222] Step 1: Data measurement using the terminal (vehicle side)

[0223] Sensors installed inside the vehicle measure the battery's temperature, voltage, current and remaining energy.

[0224] Input: Battery physical status (temperature, voltage, current, remaining energy)

[0225] Data processing: Each sensor converts analog data into digital form

[0226] Output: Battery status information as digital data

[0227] Step 2: Send data by device

[0228] The measured digital data of the battery is sent to the server at regular intervals.

[0229] Input: Digital data (temperature, voltage, current, remaining energy)

[0230] Data processing: Packetizing and encoding data

[0231] Output: Sent to the server as a communication packet

[0232] Step 3: Data reception and analysis by the server

[0233] The server analyzes the received battery data and runs an energy usage optimization algorithm.

[0234] Input: Battery data sent from the vehicle

[0235] Data computation: running energy optimization algorithms, simulating multiple scenarios

[0236] Output: Selection of optimal energy management method

[0237] Step 4: Optimization instructions generated by the server

[0238] Based on the optimal energy management method, a command is generated to be sent to the vehicle's energy management system.

[0239] Input: Result of optimal energy management method selection

[0240] Data processing: Command data generation and encoding

[0241] Output: Sends operation commands to the vehicle

[0242] Step 5: Receive and execute commands on the terminal (vehicle side)

[0243] The terminal on the vehicle receives commands sent from the server and operates the battery charging / discharging and cooling system based on those commands.

[0244] Input: Command data from the server

[0245] Data processing: Decoding and interpretation of command data

[0246] Output: Performing battery management actions (e.g., activating the cooling system)

[0247] Step 6: User monitors battery status

[0248] Users can use their smart devices to monitor battery status in real time.

[0249] Input: Battery data from the vehicle, command data from the server

[0250] Data calculation: Data display, abnormal value notification

[0251] Output: Visual information on smart devices

[0252] Step 7: User checks past historical data

[0253] Users can check past battery usage history via their smart device.

[0254] Input: Previously recorded battery data (retrieved from database)

[0255] Data calculation: Data search and display

[0256] Output: Display of analysis results

[0257] Step 8: User adjusts energy management settings

[0258] Users adjust energy management settings through their smart devices.

[0259] Input: Configuration data entered by the user

[0260] Data calculation: Processing of setting data, sending to server

[0261] Output: Applying adjusted energy management settings

[0262] Specific working example:

[0263] Example 1:

[0264] Step 1: A sensor inside the vehicle measures the battery temperature of 50°C and converts it into digital data.

[0265] Step 2: Send the converted digital data to the server.

[0266] Step 3: The server analyzes the received data and determines whether the cooling system needs to be activated.

[0267] Step 4: The server generates a "start cooling system" command and sends it to the vehicle.

[0268] Step 5: The vehicle's terminal receives the command and activates the cooling system.

[0269] Step 6: The user confirms through their smart device that the temperature has dropped from 50°C to 25°C.

[0270] Step 7: The user checks the battery temperature history on their smart device.

[0271] Step 8: The user adjusts the energy management settings to "Eco Mode."

[0272] Example 2:

[0273] The prompt text "The current battery temperature is 50°C. Please activate the cooling system." will be displayed on the smart device.

[0274] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0275] The present invention relates to an energy management system that combines a vehicle's battery system with a user's emotion engine, and in particular improves energy efficiency, enhances sustainability, and realizes energy management and in-vehicle environment optimization based on the user's emotional state.

[0276] Server Processing

[0277] The server is the heart of the present invention and performs the following processes.

[0278] 1. Receives battery measurement data (temperature, voltage, current, remaining charge) sent from the vehicle.

[0279] 2. The received measurement data is analyzed and an energy usage optimization algorithm is run, which simulates multiple scenarios, evaluates the results, and selects the optimal energy management method.

[0280] 3. Based on this, it generates and sends specific instructions to the vehicle's energy management system, such as load balancing, charging and discharging timing, and adjusting the cooling system.

[0281] 4. The user emotion engine is linked to the database to generate a user profile based on the emotional state.

[0282] Terminal (vehicle side) processing

[0283] The terminal is installed in the vehicle and performs the following processing.

[0284] 1. Measure the battery status (temperature, voltage, current, remaining capacity) through sensors and send the data to the server at regular intervals.

[0285] 2. Receive and analyze commands sent from the server, such as "reduce energy consumption for the next hour" or "start fast charging."

[0286] 3. Based on the received commands, the system performs tasks such as charging and discharging the battery, operating the cooling system, and optimizing energy consumption in real time.

[0287] 4. Using an emotion engine, the user's voice, facial expressions, and physiological data are analyzed to determine their emotional state.

[0288] 5. Adjust the entertainment and climate control systems in your vehicle based on your emotional state.

[0289] User Action

[0290] The user performs the following operations through a dedicated application.

[0291] 1. Launch the application and monitor your vehicle's battery status in real time.

[0292] 2. You can check your energy usage history through the application, such as daily energy consumption and charging / discharging schedules.

[0293] 3. Energy management settings can be adjusted through the application, such as "enable eco mode" or "delay the next charging session," allowing users to customize energy management to suit their lifestyle.

[0294] 4. The application works in conjunction with the emotion engine to display the user's emotional state in real time and suggest optimal energy management and environmental settings based on the user's emotional state.

[0295] Specific examples

[0296] For example, consider a case where a user looks tired in a car on a hot day.

[0297] Processing on the terminal (vehicle side): The vehicle's sensor detects a rise in battery temperature and sends that data (e.g., 45°C) to the server. The emotion engine also analyzes the user's facial expressions to determine their level of fatigue.

[0298] Server processing: The server receives battery data and user emotion data and uses an algorithm to calculate the optimal response, generating commands such as "activate the cooling system to lower the battery temperature," "play relaxing music on the entertainment system," and "adjust the heating and cooling system to maintain a comfortable room temperature."

[0299] Terminal processing: The vehicle's energy management system operates the cooling system based on commands from the server to maintain the battery temperature within an appropriate range, as well as regulating the entertainment system and air conditioning system.

[0300] User Action: The user can see these adjustments in real time in the application, ensuring optimal preferences are set based on their emotions.

[0301] Through this process, the system of the present invention not only significantly improves battery efficiency and sustainability, but also provides a comfortable in-car environment that responds to the user's emotional state.

[0302] The processing flow will be explained below.

[0303] Server Processing

[0304] Step 1:

[0305] The server waits for battery measurement data to be sent from the vehicle.

[0306] Step 2:

[0307] The server receives battery measurement data sent from the vehicle, including temperature, voltage, current, and remaining energy.

[0308] Step 3:

[0309] The server analyzes the received measurement data, including detecting outliers and normalizing the data.

[0310] Step 4:

[0311] The server runs an energy usage optimization algorithm based on the analyzed data, simulating multiple scenarios and evaluating the results.

[0312] Step 5:

[0313] The server selects the optimal energy management strategy and generates specific instructions based on it, including load balancing, charging and discharging timing, and cooling system adjustments.

[0314] Step 6:

[0315] The server transmits the generated command to the vehicle (terminal).

[0316] Step 7:

[0317] The server interfaces the user's emotion engine with the database to update the user profile based on the emotional state.

[0318] Terminal (vehicle side) processing

[0319] Step 1:

[0320] The device activates sensors to measure the battery's temperature, voltage, current, and remaining energy.

[0321] Step 2:

[0322] The terminal collects the measurement data from the sensors and assembles them into a single data packet.

[0323] Step 3:

[0324] The terminal transmits the measurement data to the server at regular intervals.

[0325] Step 4:

[0326] The terminal waits for a command sent from the server.

[0327] Step 5:

[0328] The terminal analyzes the command received from the server, including checking the type of command and how to execute it.

[0329] Step 6:

[0330] Based on the received instructions, the device charges and discharges the battery, activates the cooling system, and optimizes energy consumption.

[0331] Step 7:

[0332] The device uses an emotion engine to analyze the user's voice, facial expressions, and physiological data to determine their emotional state.

[0333] Step 8:

[0334] The terminal sends commands to the system to adjust the entertainment system and air conditioning system in the vehicle depending on the emotional state.

[0335] User Action

[0336] Step 1:

[0337] The user starts a dedicated application.

[0338] Step 2:

[0339] The user requests data from the server to check the current battery status from the application.

[0340] Step 3:

[0341] The user monitors the battery status displayed in the application in real time.

[0342] Step 4:

[0343] Through the application, users can check their energy usage history, including energy consumption and charging / discharging schedules.

[0344] Step 5:

[0345] The user changes the energy management settings through the application.

[0346] Step 6:

[0347] Any changes to the user's settings are sent to the server, which then readjusts the energy management algorithms based on the settings.

[0348] Step 7:

[0349] Users can see the results of the emotion engine in real time through the application.

[0350] Step 8:

[0351] The user can check the application for suggestions for optimal energy management and environmental settings based on their emotional state and make adjustments as needed.

[0352] This allows users to monitor battery status in real time and adjust energy management settings to suit their lifestyle, while the emotion engine provides adaptive environmental adjustments to provide a more comfortable driving experience.

[0353] Example 2

[0354] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0355] In modern vehicles, it is difficult to simultaneously optimize energy management and user comfort. In particular, efficient management of energy storage devices and adjustment of the in-vehicle environment based on the user's emotional state are required, but a system that controls these in an integrated manner is lacking. This leads to issues such as reduced energy efficiency and reduced user comfort.

[0356] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0357] In this invention, the server includes means for measuring the temperature, voltage, current, and remaining energy of an energy storage device in the vehicle, means for periodically transmitting measurement data from the energy storage device, means for receiving the measurement data from the energy storage device and optimizing energy use, means for simulating multiple energy consumption scenarios and evaluating the results to select an optimal energy management method, and means for detecting the emotional state of the user and adjusting environmental settings in the vehicle based on the emotional state, thereby enabling both improved energy efficiency and user comfort.

[0358] An "energy storage device" is a device for storing electricity within a vehicle, and mainly refers to batteries and capacitors.

[0359] "Measurement data" refers to data that represents physical quantities such as the temperature, voltage, current, and remaining energy of the energy storage device.

[0360] "Energy use optimization" refers to calculating and adjusting efficient energy management and usage methods based on received measurement data.

[0361] A "command" is a specific instruction sent from the server to the terminal to prompt changes to the settings of the energy storage device or the in-vehicle environment.

[0362] "Energy management system" means a system for efficiently managing the supply and use of energy in a vehicle.

[0363] "Emotional state" refers to a psychological state inferred from a user's voice, facial expression, and physiological data.

[0364] "Environmental settings" refers to settings that adjust the in-car entertainment system, air conditioning system, etc.

[0365] An "entertainment system" is a system that provides entertainment such as music playback, video playback, and games in a vehicle.

[0366] An "air conditioning system" is a system that adjusts the temperature and humidity inside a vehicle to provide a comfortable environment.

[0367] "Real-time" means that the system processes data immediately and provides information or takes action nearly instantaneously in real time.

[0368] To implement this invention, the following hardware and software are required: a sensor for measuring the status of an energy storage device installed in a vehicle, a communication module for periodically transmitting data, a server for receiving and analyzing the data, an emotion engine for analyzing the user's emotional state and adjusting the in-car environment, and a smartphone application for the user to monitor and adjust the system in real time.

[0369] The server is the heart of the present invention and performs the following functions: Receives measurement data (temperature, voltage, current, remaining charge) from the energy storage device sent from the vehicle. The received data is analyzed using machine learning algorithms using Python and TensorFlow. This optimizes energy use by simulating multiple energy consumption scenarios and selecting the optimal method. Based on the optimal energy management method selected, the server then generates and sends specific commands to the vehicle's energy management system. Examples include load balancing, charging and discharging timing, and activating the cooling system. The server also uses a user emotion engine to analyze the user's voice, facial expressions, and physiological data to generate a user profile based on their emotional state.

[0370] The terminal (vehicle side) is responsible for measuring the status of the energy storage device and periodically transmitting this data to a server. Specifically, it is equipped with sensors that measure the temperature, voltage, current, and remaining energy inside the vehicle. The data is transmitted to the server at regular intervals, and the terminal receives and analyzes commands sent from the server. These commands include reducing energy consumption and starting fast charging. Based on the received commands, the terminal then performs real-time operations such as charging and discharging, activating the cooling system, and optimizing energy consumption. The terminal also uses an emotion engine to analyze the user's voice, facial expression, and physiological data to determine their emotional state. Depending on the emotional state, the terminal adjusts the entertainment system and air conditioning system to improve user comfort.

[0371] Users operate a dedicated application on their smartphone. This application, developed using Flutter and React Native, allows them to monitor the status of the vehicle's energy management system in real time. Through the application, users can check their past energy usage history and adjust energy management settings. For example, they can set things like "enable eco mode" or "delay the next charging session." In addition, the application works with an emotion engine to display the user's emotional state in real time and suggests optimal energy management and environmental settings based on their emotional state.

[0372] As a concrete example, consider a case where a user looks tired while in the car on a hot day. At this time, a sensor on the device (in the vehicle) detects a rise in battery temperature and sends that data (e.g., 45°C) to the server. The emotion engine also analyzes the user's facial expression and determines the level of fatigue. The server receives this data and, based on the analysis results, generates commands such as "activate the cooling system," "play relaxing music," and "set the room temperature to a comfortable level." These commands are sent to the device, which then operates the cooling system, adjusts the entertainment system, and sets the air conditioning system in accordance with the commands. The user can then check these adjustments on their smartphone application and confirm that the optimal environmental settings based on their emotional state have been implemented.

[0373] Examples of input prompts for a generative AI model include:

[0374] Please explain the detailed operational flow of the energy management system in a situation where the user looks tired in the car on a hot day. Please explain each step specifically from the perspective of the server, the terminal (in the car), and the user.

[0375] As described above, the present invention can be implemented by integrating various hardware and software in order to achieve both efficient management of the energy storage device and user comfort.

[0376] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0377] Step 1:

[0378] Battery status measurement and data transmission on the terminal (vehicle side)

[0379] The terminal (vehicle side) uses sensors installed inside the vehicle to measure the temperature, voltage, current, and remaining energy of the energy storage device. The measurement data is collected, for example, every 10 minutes. This data is collected in the telematics unit via the vehicle's CAN bus and periodically sent to the server.

[0380] Input: Battery measurement data from in-vehicle sensors (temperature, voltage, current, remaining capacity)

[0381] Data processing or data calculation: Aggregation of measurement data, shaping of time series data

[0382] Output: Transmission of measurement data from the telematics unit to the server

[0383] Step 2:

[0384] Server data reception and analysis

[0385] The server receives measurement data sent from the terminal (vehicle side). After receiving this data, it is stored in a database and an energy usage optimization algorithm is executed. A machine learning algorithm using Python and TensorFlow analyzes the measurement data and calculates the optimal energy management method.

[0386] Input: Measurement data sent from the device (temperature, voltage, current, remaining capacity)

[0387] Data processing or data calculation: receiving data, storing it in a database, and analyzing it with machine learning algorithms

[0388] Output: Calculation results of optimal energy management method

[0389] Step 3:

[0390] Server command generation

[0391] The server generates specific commands based on the analysis results. These commands include, for example, "reduce energy consumption for the next hour," "start rapid charging," and "activate the cooling system." These commands are then sent back to the terminal (vehicle side).

[0392] Input: Calculation result of optimal energy management method

[0393] Data processing or data calculation: Creation of specific commands using command generation logic

[0394] Output: Specific instructions sent to the terminal

[0395] Step 4:

[0396] Terminal (vehicle side) command reception and execution

[0397] The device receives and analyzes instructions sent from the server, and based on the instructions, performs operations in real time, such as charging and discharging the battery, activating the cooling system, and optimizing energy consumption.

[0398] Input: Specific instructions sent by the server

[0399] Data processing or data calculation: parsing commands and executing control logic for battery management systems and cooling systems

[0400] Output: Specific operation (start of charging / discharging, start of cooling system, etc.)

[0401] Step 5:

[0402] Emotion analysis on the device (vehicle side)

[0403] The device uses cameras and microphones inside the vehicle to collect the user's voice, facial expressions, and physiological data, and analyzes them using an emotion engine. Based on the analysis results, the device determines the user's emotional state.

[0404] Input: User voice, facial expressions, physiological data

[0405] Data processing or data calculation: Emotion analysis using image processing software (OpenCV) and voice analysis tool (Praat)

[0406] Output: Determined user's emotional state

[0407] Step 6:

[0408] Terminal (vehicle side) environment adjustment

[0409] Based on the emotion analysis results, the device can adjust the vehicle's entertainment and climate control systems, for example, playing relaxing music and setting the temperature to a comfortable level if the user is tired.

[0410] Input: Emotion analysis results, environmental adjustment instructions from the server

[0411] Data processing or data calculation: Executing control logic for entertainment systems or air conditioning systems

[0412] Output: Controlled in-car environment (playing music, changing climate settings, etc.)

[0413] Step 7:

[0414] Real-time user monitoring and configuration adjustment

[0415] Users can monitor the status of their vehicle's energy management system in real time and check past energy usage history through a smartphone application. They can also adjust energy management settings through the application, such as enabling Eco Mode or delaying the next charging session.

[0416] Input: Status data from the vehicle's energy management system, user configuration change requests

[0417] Data processing or data calculation: Visualization of status data, execution of energy management setting logic

[0418] Output: Real-time monitoring screen, setting change results

[0419] This completes a series of processes, enabling efficient management of the vehicle's energy storage device and providing a comfortable in-vehicle environment that suits the user's emotional state.

[0420] (Application example 2)

[0421] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0422] Vehicle energy management systems are required to improve battery energy efficiency and realize an optimal in-car environment that responds to the user's emotional state. It is also important that real-time battery status monitoring and energy management settings are easy for users to understand and operate intuitively. To solve these issues, energy management based on the user's emotional state is necessary in addition to optimizing energy use.

[0423] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving battery data transmitted from the vehicle and optimizing energy use, means for analyzing the user's emotional state and generating commands based on the emotional state, and means for generating prompt sentences to be input to the generative AI model. This makes it possible to use energy efficiently and provide a comfortable in-vehicle environment based on the user's emotions.

[0424] "Battery measurement data" refers to various indicators such as the temperature, voltage, current, and remaining energy of the battery inside the vehicle.

[0425] "Energy use optimization" refers to the process of planning and implementing efficient energy usage methods based on battery data.

[0426] An "energy management system" is a system that optimally controls and manages various energy systems, including batteries, inside a vehicle.

[0427] The "user's emotional state" refers to the emotions expressed by the user, and is analyzed from voice, facial expressions, physiological data, and the like.

[0428] "Emotion analysis software" is software that analyzes a user's facial expressions and voice data to determine their emotional state.

[0429] "Real-time execution" means that the entire process, from data acquisition to processing to command execution, occurs with almost no delay.

[0430] A "generative AI model" is a model of artificial intelligence that is trained to perform a specific task.

[0431] A "prompt" is an instruction or question that is input into a generative AI model.

[0432] To implement this invention, the system provides a technology for efficiently managing the battery status in a vehicle and optimizing the in-vehicle environment based on the emotional state of the user. The system configuration and processing details are described below.

[0433] System Program Overview

[0434] This system consists of three main elements: a server, a terminal (in the vehicle), and a user.

[0435] Server Processing

[0436] The server is the center of the system and performs the following processes:

[0437] 1. Receiving and analyzing battery data:

[0438] Receives battery measurement data (temperature, voltage, current, remaining energy) sent from the vehicle.

[0439] It analyzes the received battery data and runs energy usage optimization algorithms.

[0440] 2. Optimizing energy use:

[0441] Multiple scenarios are simulated, the results are evaluated, and the optimal energy management method is selected.

[0442] Based on the optimization results, specific instructions are generated and sent to the vehicle's energy management system.

[0443] 3. Emotion data analysis and command generation:

[0444] Emotion analysis software is used to analyze the user's facial expressions and voice to determine their emotional state.

[0445] Generates commands to entertainment and air conditioning systems based on emotional state.

[0446] 4. Prompt generation:

[0447] Generate prompt sentences to input to the generative AI model.

[0448] Terminal (vehicle side) processing

[0449] The terminal is installed in the vehicle and performs the following processes.

[0450] 1. Battery data measurement and transmission:

[0451] Sensors measure the battery's status (temperature, voltage, current, remaining energy) and periodically send the data to a server.

[0452] 2. Receiving and executing orders:

[0453] Receives and analyzes instructions sent from the server.

[0454] Based on the received commands, it adjusts battery charging and discharging, cooling system operation, and entertainment and air conditioning systems in real time.

[0455] User Action

[0456] The user performs the following operations through a dedicated application.

[0457] 1. Battery status monitoring:

[0458] Launch the application and monitor your vehicle's battery status in real time.

[0459] You can check your past energy usage history through the application.

[0460] 2. Adjust Energy Management Settings:

[0461] Adjust energy management settings, such as "Enable Eco Mode" or "Delay next charging session."

[0462] 3. Reflection of emotional state:

[0463] Optimal energy management and environmental settings are suggested based on the user's emotional state.

[0464] Specific examples

[0465] For example, consider a case where a user looks tired in a car on a hot day.

[0466] 1. Terminal (vehicle side) processing:

[0467] Sensors in the vehicle measure the battery temperature and send the data to a server, while emotion analysis software determines the user's level of fatigue.

[0468] 2. Server processing:

[0469] The server analyzes battery data and emotional data and generates commands such as "start the cooling system," "play relaxing music," and "adjust the air conditioning system."

[0470] 3. Terminal processing:

[0471] The vehicle's energy management system regulates the cooling system, entertainment system, and air conditioning system based on commands from the server.

[0472] Prompt Sentence Examples

[0473] "The battery temperature of the autonomous vehicle has reached 45°C. The user's facial expression indicates that they are tired. Please generate optimal commands."

[0474] In this way, the system of the present invention realizes efficient energy utilization and provides a comfortable in-vehicle environment based on the user's emotions.

[0475] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0476] Step 1: Measuring and sending battery data

[0477] The terminal (vehicle side) uses sensors installed inside the vehicle to measure various indicators such as the battery temperature, voltage, current, and remaining energy. The measured data is sent to the server at regular intervals. The input is the measurement data from the sensors, and the output is the battery data sent to the server.

[0478] Step 2: Receiving and analyzing battery data

[0479] The server receives battery data sent from the vehicle. The received data is analyzed and an energy usage optimization algorithm is executed. The input is the battery data sent from the terminal, and the output is the analysis result and the energy management optimization result.

[0480] Step 3: Optimize energy use

[0481] The server simulates multiple scenarios, evaluates the results, and selects the optimal energy management method. Based on the optimization results, it generates and sends specific instructions. The input is the analyzed battery data, and the output is the optimal energy management method and the corresponding instructions.

[0482] Step 4: Collect and analyze emotion data

[0483] The terminal (in the vehicle) uses cameras and microphones inside the vehicle to collect the user's facial expressions and voice. This data is analyzed by emotion analysis software to determine the user's emotional state. The input is the facial expression and voice data collected by the camera and microphone, and the output is the determined emotional state data.

[0484] Step 5: Command generation based on emotional state

[0485] The server receives the emotion analysis results and generates specific commands for the entertainment system and air conditioning system based on the emotional state. These commands are also sent to the energy management system. The input is the emotion analysis results, and the output is adjustment commands for the entertainment system and air conditioning system.

[0486] Step 6: Execute the directive

[0487] The terminal (on the vehicle side) receives commands from the server and adjusts battery charging / discharging, cooling system operation, entertainment system, and air conditioning system in real time. The input is the command from the server, and the output is the execution result of battery management and environmental adjustment.

[0488] Step 7: Monitor your battery status and adjust settings

[0489] Users can monitor the vehicle's battery status in real time through a dedicated application, and can also use the application to adjust energy management settings. The input is the operating data through the application, and the output is the adjusted energy management settings.

[0490] Step 8: Generate a prompt statement

[0491] The server generates a prompt sentence to be input to the generative AI model. This prompt sentence is generated in an appropriate form based on the overall command of the system. The input is the system state and command data, and the output is the generated prompt sentence.

[0492] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0493] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0494] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0495] [Second embodiment]

[0496] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0497] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0498] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0499] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0500] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0501] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0502] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0503] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0504] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0505] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0506] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0507] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0508] The present invention relates to battery systems in vehicles, and in particular to a system for improving energy efficiency and sustainability, which includes technology for monitoring the battery's condition in real time and achieving optimal energy usage.

[0509] Server Processing

[0510] The server is the heart of the present invention and performs the following processes.

[0511] 1. Receives battery measurement data (temperature, voltage, current, remaining charge) sent from the vehicle.

[0512] 2. The received measurement data is analyzed and an energy usage optimization algorithm is run, which simulates multiple scenarios, evaluates the results, and selects the optimal energy management method.

[0513] 3. Based on this selection, specific instructions are generated and sent to the vehicle's energy management system, such as load balancing, charging / discharging timing, and cooling system adjustments.

[0514] Terminal (vehicle side) processing

[0515] The terminal is installed in the vehicle and performs the following processing.

[0516] 1. Measure the battery status (temperature, voltage, current, remaining capacity) through sensors and send the data to the server at regular intervals.

[0517] 2. Receive and analyze commands sent from the server, such as "reduce energy consumption for the next hour" or "start fast charging."

[0518] 3. Based on the received commands, the system performs tasks such as charging and discharging the battery, operating the cooling system, and optimizing energy consumption in real time.

[0519] User Action

[0520] The user performs the following operations through a dedicated application.

[0521] 1. Launch the application and monitor your vehicle's battery status in real time.

[0522] 2. You can check your energy usage history through the application, such as daily energy consumption and charging / discharging schedules.

[0523] 3. Energy management settings can be adjusted through the application, such as "enable eco mode" or "delay the next charging session," allowing users to customize energy management to suit their lifestyle.

[0524] Specific examples

[0525] For example, consider the case where a vehicle's battery temperature rises on a hot day.

[0526] Terminal (vehicle side) processing: The vehicle's sensor detects a rise in battery temperature and sends that data (e.g., 45°C) to the server.

[0527] Server processing: The server receives this data and uses an algorithm to calculate the optimal course of action, resulting in a command to "activate the cooling system to lower the battery temperature."

[0528] Terminal processing: Based on the received command, the vehicle's energy management system activates the cooling system to maintain the battery temperature within an appropriate range.

[0529] User Action: The user can view this information in real time in the application. For example, the user can see that the battery temperature has dropped from 45°C to 25°C.

[0530] Through this process, the system of the present invention significantly improves battery efficiency and sustainability, extending vehicle range and battery life.

[0531] The processing flow will be explained below.

[0532] Server Processing

[0533] Step 1:

[0534] The server waits for battery measurement data to be sent from the vehicle.

[0535] Step 2:

[0536] The server receives battery measurement data sent from the vehicle, including temperature, voltage, current, and remaining energy.

[0537] Step 3:

[0538] The server analyzes the received measurement data, which includes outlier detection and data normalization.

[0539] Step 4:

[0540] The server runs an energy usage optimization algorithm based on the analyzed data, simulating multiple scenarios and evaluating the results.

[0541] Step 5:

[0542] The server selects the optimal energy management strategy and generates specific instructions based on it, including load balancing, charging and discharging timing, and cooling system adjustments.

[0543] Step 6:

[0544] The server transmits the generated command to the vehicle (terminal).

[0545] Terminal (vehicle side) processing

[0546] Step 1:

[0547] The device activates sensors to measure the battery's temperature, voltage, current, and remaining energy.

[0548] Step 2:

[0549] The terminal collects the measurement data from the sensors and assembles them into a single data packet.

[0550] Step 3:

[0551] The terminal transmits the measurement data to the server at regular intervals.

[0552] Step 4:

[0553] The terminal waits for a command sent from the server.

[0554] Step 5:

[0555] The terminal analyzes the command received from the server, including checking the type of command and how to execute it.

[0556] Step 6:

[0557] Based on the received instructions, the device charges and discharges the battery, activates the cooling system, and optimizes energy consumption.

[0558] User Action

[0559] Step 1:

[0560] The user starts a dedicated application.

[0561] Step 2:

[0562] The user requests data from the server to check the current battery status from the application.

[0563] Step 3:

[0564] The user monitors the battery status displayed in the application in real time.

[0565] Step 4:

[0566] Through the application, users can check their energy usage history, including energy consumption and charging / discharging schedules.

[0567] Step 5:

[0568] The user changes the energy management settings through the application.

[0569] Step 6:

[0570] Any changes to the user's settings are sent to the server, which then readjusts the energy management algorithms based on the settings.

[0571] This allows users to monitor battery status in real time and adjust energy management settings to suit their lifestyle.

[0572] Example 1

[0573] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0574] The aim of this invention is to improve the energy efficiency and sustainability of in-vehicle battery systems. However, conventional systems do not adequately monitor battery status in real time and perform data analysis and optimization algorithms to optimize energy usage. As a result, efficient battery use and extended battery life have been challenges.

[0575] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0576] In this invention, the server includes means for receiving measurement data and storing it in a database, means for analyzing the stored measurement data, and means for executing an energy usage optimization algorithm based on the analysis results, thereby enabling real-time monitoring of the battery status, selecting an optimal energy management method, and generating and transmitting commands, thereby enabling efficient use of the battery and extending its lifespan.

[0577] A "vehicle" is a machine that has a battery inside and moves by consuming energy.

[0578] A "battery" is a device that converts chemical energy into electrical energy and provides power for a period of time.

[0579] "Measurement data" is numerical data that indicates information about the state of the battery, and specifically includes temperature, voltage, current, and remaining energy.

[0580] A "server" is a computer system that receives, stores, analyzes, and processes data as needed.

[0581] A "database" is an information system for efficiently storing and managing large amounts of data.

[0582] "Analysis" is the act of evaluating and understanding the state and characteristics of an object based on collected data.

[0583] An "optimization algorithm" is a computational procedure for maximizing or minimizing the performance of a goal while taking into account multiple criteria.

[0584] A "command" is a specific operation instruction sent from the server to the terminal.

[0585] An "energy management system" is a system for managing and optimizing the energy consumption of batteries and vehicles.

[0586] "Real-time" refers to the immediate reflection of current status and behavior.

[0587] The present invention relates to a battery system in a vehicle, and in particular to a system for improving energy efficiency and sustainability, including technology for monitoring the state of the vehicle battery in real time to achieve optimal energy usage.

[0588] Server Processing

[0589] The server is the heart of the invention, receiving battery measurement data (temperature, voltage, current, remaining charge) sent from the vehicle and storing it in a database. The server uses MySQL or PostgreSQL as its database management system (DBMS). The stored data is analyzed and an energy usage optimization algorithm is executed. This algorithm simulates multiple scenarios and evaluates the results to select the optimal energy management method. Analysis tools such as Python's Pandas and NumPy are used for the analysis. Based on the results, specific commands (e.g., load balancing, charging / discharging timing, and cooling system adjustment) are generated and sent to the vehicle's energy management system.

[0590] Terminal (vehicle side) processing

[0591] The terminal is installed inside the vehicle and measures the battery condition through sensors, periodically sending the data to the server. A communications library is used to send the data. The terminal also receives and analyzes commands sent from the server. This analysis includes parsing the data and judging various conditions. Based on the received commands, the terminal performs real-time operations such as charging and discharging the battery, operating the cooling system, and optimizing energy consumption.

[0592] User Action

[0593] Users can monitor their vehicle's battery status in real time through a dedicated application. This application runs on a mobile device and provides the vehicle's battery status. Users can also check their past energy usage history through the application. Specifically, this includes functions to display daily energy consumption and charging / discharging schedules. In addition, they can adjust energy management settings. For example, they can enable Eco Mode or delay the next charging session.

[0594] Specific examples

[0595] For example, consider the case where a vehicle's battery temperature rises on a hot day. The device's sensor detects the rise in battery temperature and sends that data (for example, 45°C) to the server. The server receives this data, uses an algorithm to calculate the optimal response, and generates a command to "activate the cooling system to lower the battery temperature." Based on the received command, the vehicle's energy management system activates the cooling system to maintain the battery temperature within an appropriate range. The user can check this information in real time in the application. For example, they can see that the battery temperature has dropped from 45°C to 25°C.

[0596] Prompt Sentence Examples

[0597] Example prompts to input to a generative AI model:

[0598] Please write a description of the functionality of a vehicle's battery management system, including how sensors measure battery status and send that data to a server for analysis and optimization. Also, please include functionality that allows users to monitor battery status and adjust energy management through an application.

[0599] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0600] Step 1:

[0601] Server data reception

[0602] Input: Battery measurement data sent from the vehicle (temperature, voltage, current, remaining energy)

[0603] Processing: The server receives this data via HTTP communication. Specifically, the communication module parses and validates the received data.

[0604] Output: Measurement data in a format suitable for analysis

[0605] Step 2:

[0606] Server database storage

[0607] Input: Measurement data in a format suitable for analysis

[0608] Processing: The server stores the received data in a database and executes SQL queries using MySQL or PostgreSQL as the database management system (DBMS).

[0609] Output: Measurement data stored in a database

[0610] Step 3:

[0611] Server data analysis

[0612] Input: Measurement data stored in the database

[0613] Processing: The server uses Python's Pandas and NumPy to analyze the stored data, including calculating the mean, standard deviation, and outlier detection.

[0614] Output: Parsed battery data

[0615] Step 4:

[0616] Optimization algorithm execution on the server

[0617] Input: Parsed battery data

[0618] Processing: The server runs an energy usage optimization algorithm based on the analysis results. This algorithm uses Gurobi and SciPy to simulate multiple scenarios and select the optimal energy management method.

[0619] Output: Optimized energy management methods and specific directives

[0620] Step 5:

[0621] Server command generation and transmission

[0622] Input: Optimized energy management methods and specific directives

[0623] Processing: The server formats the command in JSON format and sends it to the vehicle's terminal via HTTP communication.

[0624] Output: Commands sent to the vehicle's terminal

[0625] Step 6:

[0626] Device sensor data measurement

[0627] Input: None

[0628] Processing: The terminal measures the battery status (temperature, voltage, current, remaining energy) using sensors in the vehicle, including temperature, voltage, and current sensors.

[0629] Output: Measured battery data

[0630] Step 7:

[0631] Data transmission from the device

[0632] Input: Measured battery data

[0633] Processing: The device sends the data to the server by performing an HTTP POST request using a communication library.

[0634] Output: Battery data sent to the server

[0635] Step 8:

[0636] Terminal command reception and analysis

[0637] Input: Command sent from the server

[0638] Processing: The device receives the command, analyzes the command content, parses the JSON format data, and makes a decision based on various conditions.

[0639] Output: Parsed command content

[0640] Step 9:

[0641] Terminal command execution

[0642] Input: Parsed command content

[0643] Processing: Based on the received instructions, the device will charge and discharge the battery, activate the cooling system, and optimize energy consumption in real time, such as activating the cooling system and adjusting the charging schedule.

[0644] Output: Energy management operations performed

[0645] Step 10:

[0646] Real-time user monitoring

[0647] Input: Battery data

[0648] Processing: The user launches a dedicated application, which retrieves the latest battery data from the server and displays it.

[0649] Output: Real-time updated battery status

[0650] Step 11:

[0651] Check user's past data

[0652] Input: Battery usage history for a user-specified period

[0653] Processing: The application retrieves historical data from the server and displays it to the user in the form of graphs and lists.

[0654] Output: Display of past energy usage history

[0655] Step 12:

[0656] Adjusting User Settings

[0657] Input: Energy management settings changed by the user

[0658] Processing: The user adjusts the energy management settings through the application's settings screen and sends the settings to the server.

[0659] Output: Updated Energy Management Settings

[0660] (Application example 1)

[0661] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0662] Conventional vehicle battery systems lack the technology to monitor battery status in real time and perform optimal energy management. They also lack sufficient means to provide users with timely energy management information, such as notifications of abnormal values ​​or displaying past usage history. Another issue is that it is difficult for users to adjust energy management settings via smart devices.

[0663] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0664] In this invention, the server includes a means for receiving battery measurement data and optimizing energy use, a means for sending commands to the vehicle's energy management system based on the energy use optimization, a means for displaying battery measurement data on the smart device in real time, a means for notifying of abnormal values, a means for presenting the battery energy management status as alerts or commands via the smart device, and a means for retrieving and displaying past battery usage history from a database. This enables optimal energy management by monitoring the battery status in real time and immediately notifying the user if an abnormality occurs. Furthermore, the user can easily check past usage history and adjust energy management settings via the smart device.

[0665] "Battery temperature" refers to the degree of thermal energy currently held by the battery in the vehicle.

[0666] "Voltage" refers to the potential difference produced by a vehicle's battery.

[0667] "Current" is a quantity that indicates the flow of electrons from a battery in a vehicle.

[0668] "Remaining energy" is the total amount of energy currently remaining in the vehicle's battery.

[0669] "Measurement data" refers to information about the battery's temperature, voltage, current, and remaining energy.

[0670] The "transmission means" is a communication means for sending the measurement data to the server.

[0671] The "optimization means" is a means for executing an algorithm to improve the efficiency of energy use based on the measurement data.

[0672] A "command" is an operational instruction sent to the energy management system.

[0673] A "smart device" is a multi-function device that has the ability to connect to the Internet and run applications.

[0674] The "real-time display means" is a means for displaying battery measurement data on a smart device in real time.

[0675] The "abnormal value notification means" is a means for notifying when an abnormality in the battery state is detected.

[0676] The "energy management status presentation means" is a means for presenting the optimization status of energy usage to the user as alerts or instructions via a smart device.

[0677] "Past usage history" refers to data on the battery's past voltage, current, temperature, and remaining energy.

[0678] A "database" is an information storage means for recording and saving past usage history.

[0679] This invention relates to a battery system for autonomous vehicles, and in particular to a system for improving energy efficiency and sustainability. The system measures the temperature, voltage, current, and remaining energy of the vehicle battery in real time, enabling optimal energy management.

[0680] Server Processing

[0681] The server is the core of the present invention and performs the following processes: First, it receives battery measurement data (temperature, voltage, current, remaining charge) sent from the vehicle. It analyzes this data and runs an energy usage optimization algorithm. The hardware and software used include cloud servers (e.g., AWS Lambda, Google Cloud Functions). The algorithm simulates multiple scenarios, evaluates the results, and selects the optimal energy management method. Finally, it generates and sends commands to the vehicle's energy management system based on the optimization results.

[0682] Terminal (vehicle side) processing

[0683] The terminal is installed inside the vehicle and measures the battery's status (temperature, voltage, current, remaining charge) through sensors, sending the data to a server at regular intervals. This data is displayed in real time mainly through smart devices. It also receives commands sent from the server and, based on those commands, performs tasks such as charging and discharging the battery, operating the cooling system, and optimizing energy consumption. The hardware used consists of a sensor system and communication module inside the vehicle.

[0684] User Action

[0685] Users use a dedicated smart device (e.g., smart glasses or a smartphone) to perform the following processes. First, the smart device has a function to display battery measurement data in real time. If an abnormal value is detected, an alert will be sent. In addition, past battery usage history can be retrieved from a database and easily checked through the smart device. Furthermore, users can adjust energy management settings through the smart device, which allows energy management to be optimized to suit their individual usage conditions.

[0686] Specific examples

[0687] If the battery temperature rises on a hot day, the following process occurs: The device's sensor detects a rise in battery temperature (e.g., 50°C) and sends the data to the server. The server receives this data and generates a command to activate the cooling system. This command activates the vehicle's cooling system, maintaining the battery temperature within an appropriate range (e.g., 25°C to 45°C). The user can check the change in battery temperature in real time through the smart glasses. Furthermore, if an abnormal value is detected, a prompt message will be displayed: "The current battery temperature is 50°C. Please activate the cooling system."

[0688] This allows the system of the present invention to significantly improve battery efficiency and sustainability, extending vehicle range and battery life.

[0689] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0690] Specific explanation of processing steps

[0691] Step 1: Data measurement using the terminal (vehicle side)

[0692] Sensors installed inside the vehicle measure the battery's temperature, voltage, current and remaining energy.

[0693] Input: Battery physical status (temperature, voltage, current, remaining energy)

[0694] Data processing: Each sensor converts analog data into digital form

[0695] Output: Battery status information as digital data

[0696] Step 2: Send data by device

[0697] The measured digital data of the battery is sent to the server at regular intervals.

[0698] Input: Digital data (temperature, voltage, current, remaining energy)

[0699] Data processing: Packetizing and encoding data

[0700] Output: Sent to the server as a communication packet

[0701] Step 3: Data reception and analysis by the server

[0702] The server analyzes the received battery data and runs an energy usage optimization algorithm.

[0703] Input: Battery data sent from the vehicle

[0704] Data computation: running energy optimization algorithms, simulating multiple scenarios

[0705] Output: Selection of optimal energy management method

[0706] Step 4: Optimization instructions generated by the server

[0707] Based on the optimal energy management method, a command is generated to be sent to the vehicle's energy management system.

[0708] Input: Result of optimal energy management method selection

[0709] Data processing: Command data generation and encoding

[0710] Output: Sends operation commands to the vehicle

[0711] Step 5: Receive and execute commands on the terminal (vehicle side)

[0712] The terminal on the vehicle receives commands sent from the server and operates the battery charging / discharging and cooling system based on those commands.

[0713] Input: Command data from the server

[0714] Data processing: Decoding and interpretation of command data

[0715] Output: Performing battery management actions (e.g., activating the cooling system)

[0716] Step 6: User monitors battery status

[0717] Users can use their smart devices to monitor battery status in real time.

[0718] Input: Battery data from the vehicle, command data from the server

[0719] Data calculation: Data display, abnormal value notification

[0720] Output: Visual information on smart devices

[0721] Step 7: User checks past historical data

[0722] Users can check past battery usage history via their smart device.

[0723] Input: Previously recorded battery data (retrieved from database)

[0724] Data calculation: Data search and display

[0725] Output: Display of analysis results

[0726] Step 8: User adjusts energy management settings

[0727] Users adjust energy management settings through their smart devices.

[0728] Input: Configuration data entered by the user

[0729] Data calculation: Processing of setting data, sending to server

[0730] Output: Applying adjusted energy management settings

[0731] Specific working example:

[0732] Example 1:

[0733] Step 1: A sensor inside the vehicle measures the battery temperature of 50°C and converts it into digital data.

[0734] Step 2: Send the converted digital data to the server.

[0735] Step 3: The server analyzes the received data and determines whether the cooling system needs to be activated.

[0736] Step 4: The server generates a "start cooling system" command and sends it to the vehicle.

[0737] Step 5: The vehicle's terminal receives the command and activates the cooling system.

[0738] Step 6: The user confirms through their smart device that the temperature has dropped from 50°C to 25°C.

[0739] Step 7: The user checks the battery temperature history on their smart device.

[0740] Step 8: The user adjusts the energy management settings to "Eco Mode."

[0741] Example 2:

[0742] The prompt text "The current battery temperature is 50°C. Please activate the cooling system." will be displayed on the smart device.

[0743] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0744] The present invention relates to an energy management system that combines a vehicle's battery system with a user's emotion engine, and in particular improves energy efficiency, enhances sustainability, and realizes energy management and in-vehicle environment optimization based on the user's emotional state.

[0745] Server Processing

[0746] The server is the heart of the present invention and performs the following processes.

[0747] 1. Receives battery measurement data (temperature, voltage, current, remaining charge) sent from the vehicle.

[0748] 2. The received measurement data is analyzed and an energy usage optimization algorithm is run, which simulates multiple scenarios, evaluates the results, and selects the optimal energy management method.

[0749] 3. Based on this, it generates and sends specific instructions to the vehicle's energy management system, such as load balancing, charging and discharging timing, and adjusting the cooling system.

[0750] 4. The user emotion engine is linked to the database to generate a user profile based on the emotional state.

[0751] Terminal (vehicle side) processing

[0752] The terminal is installed in the vehicle and performs the following processing.

[0753] 1. Measure the battery status (temperature, voltage, current, remaining capacity) through sensors and send the data to the server at regular intervals.

[0754] 2. Receive and analyze commands sent from the server, such as "reduce energy consumption for the next hour" or "start fast charging."

[0755] 3. Based on the received commands, the system performs tasks such as charging and discharging the battery, operating the cooling system, and optimizing energy consumption in real time.

[0756] 4. Using an emotion engine, the user's voice, facial expressions, and physiological data are analyzed to determine their emotional state.

[0757] 5. Adjust the entertainment and climate control systems in your vehicle based on your emotional state.

[0758] User Action

[0759] The user performs the following operations through a dedicated application.

[0760] 1. Launch the application and monitor your vehicle's battery status in real time.

[0761] 2. You can check your energy usage history through the application, such as daily energy consumption and charging / discharging schedules.

[0762] 3. Energy management settings can be adjusted through the application, such as "enable eco mode" or "delay the next charging session," allowing users to customize energy management to suit their lifestyle.

[0763] 4. The application works in conjunction with the emotion engine to display the user's emotional state in real time and suggest optimal energy management and environmental settings based on the user's emotional state.

[0764] Specific examples

[0765] For example, consider a case where a user looks tired in a car on a hot day.

[0766] Processing on the terminal (vehicle side): The vehicle's sensor detects a rise in battery temperature and sends that data (e.g., 45°C) to the server. The emotion engine also analyzes the user's facial expressions to determine their level of fatigue.

[0767] Server processing: The server receives battery data and user emotion data and uses an algorithm to calculate the optimal response, generating commands such as "activate the cooling system to lower the battery temperature," "play relaxing music on the entertainment system," and "adjust the heating and cooling system to maintain a comfortable room temperature."

[0768] Terminal processing: The vehicle's energy management system operates the cooling system based on commands from the server to maintain the battery temperature within an appropriate range, as well as regulating the entertainment system and air conditioning system.

[0769] User Action: The user can see these adjustments in real time in the application, ensuring optimal preferences are set based on their emotions.

[0770] Through this process, the system of the present invention not only significantly improves battery efficiency and sustainability, but also provides a comfortable in-car environment that responds to the user's emotional state.

[0771] The processing flow will be explained below.

[0772] Server Processing

[0773] Step 1:

[0774] The server waits for battery measurement data to be sent from the vehicle.

[0775] Step 2:

[0776] The server receives battery measurement data sent from the vehicle, including temperature, voltage, current, and remaining energy.

[0777] Step 3:

[0778] The server analyzes the received measurement data, including detecting outliers and normalizing the data.

[0779] Step 4:

[0780] The server runs an energy usage optimization algorithm based on the analyzed data, simulating multiple scenarios and evaluating the results.

[0781] Step 5:

[0782] The server selects the optimal energy management strategy and generates specific instructions based on it, including load balancing, charging and discharging timing, and cooling system adjustments.

[0783] Step 6:

[0784] The server transmits the generated command to the vehicle (terminal).

[0785] Step 7:

[0786] The server interfaces the user's emotion engine with the database to update the user profile based on the emotional state.

[0787] Terminal (vehicle side) processing

[0788] Step 1:

[0789] The device activates sensors to measure the battery's temperature, voltage, current, and remaining energy.

[0790] Step 2:

[0791] The terminal collects the measurement data from the sensors and assembles them into a single data packet.

[0792] Step 3:

[0793] The terminal transmits the measurement data to the server at regular intervals.

[0794] Step 4:

[0795] The terminal waits for a command sent from the server.

[0796] Step 5:

[0797] The terminal analyzes the command received from the server, including checking the type of command and how to execute it.

[0798] Step 6:

[0799] Based on the received instructions, the device charges and discharges the battery, activates the cooling system, and optimizes energy consumption.

[0800] Step 7:

[0801] The device uses an emotion engine to analyze the user's voice, facial expressions, and physiological data to determine their emotional state.

[0802] Step 8:

[0803] The terminal sends commands to the system to adjust the entertainment system and air conditioning system in the vehicle depending on the emotional state.

[0804] User Action

[0805] Step 1:

[0806] The user starts a dedicated application.

[0807] Step 2:

[0808] The user requests data from the server to check the current battery status from the application.

[0809] Step 3:

[0810] The user monitors the battery status displayed in the application in real time.

[0811] Step 4:

[0812] Through the application, users can check their energy usage history, including energy consumption and charging / discharging schedules.

[0813] Step 5:

[0814] The user changes the energy management settings through the application.

[0815] Step 6:

[0816] Any changes to the user's settings are sent to the server, which then readjusts the energy management algorithms based on the settings.

[0817] Step 7:

[0818] Users can see the results of the emotion engine in real time through the application.

[0819] Step 8:

[0820] The user can check the application for suggestions for optimal energy management and environmental settings based on their emotional state and make adjustments as needed.

[0821] This allows users to monitor battery status in real time and adjust energy management settings to suit their lifestyle, while the emotion engine provides adaptive environmental adjustments to provide a more comfortable driving experience.

[0822] Example 2

[0823] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0824] In modern vehicles, it is difficult to simultaneously optimize energy management and user comfort. In particular, efficient management of energy storage devices and adjustment of the in-vehicle environment based on the user's emotional state are required, but a system that controls these in an integrated manner is lacking. This leads to issues such as reduced energy efficiency and reduced user comfort.

[0825] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0826] In this invention, the server includes means for measuring the temperature, voltage, current, and remaining energy of an energy storage device in the vehicle, means for periodically transmitting measurement data from the energy storage device, means for receiving the measurement data from the energy storage device and optimizing energy use, means for simulating multiple energy consumption scenarios and evaluating the results to select an optimal energy management method, and means for detecting the emotional state of the user and adjusting environmental settings in the vehicle based on the emotional state, thereby enabling both improved energy efficiency and user comfort.

[0827] An "energy storage device" is a device for storing electricity within a vehicle, and mainly refers to batteries and capacitors.

[0828] "Measurement data" refers to data that represents physical quantities such as the temperature, voltage, current, and remaining energy of the energy storage device.

[0829] "Energy use optimization" refers to calculating and adjusting efficient energy management and usage methods based on received measurement data.

[0830] A "command" is a specific instruction sent from the server to the terminal to prompt changes to the settings of the energy storage device or the in-vehicle environment.

[0831] "Energy management system" means a system for efficiently managing the supply and use of energy in a vehicle.

[0832] "Emotional state" refers to a psychological state inferred from a user's voice, facial expression, and physiological data.

[0833] "Environmental settings" refers to settings that adjust the in-car entertainment system, air conditioning system, etc.

[0834] An "entertainment system" is a system that provides entertainment such as music playback, video playback, and games in a vehicle.

[0835] An "air conditioning system" is a system that adjusts the temperature and humidity inside a vehicle to provide a comfortable environment.

[0836] "Real-time" means that the system processes data immediately and provides information or takes action nearly instantaneously in real time.

[0837] To implement this invention, the following hardware and software are required: a sensor for measuring the status of an energy storage device installed in a vehicle, a communication module for periodically transmitting data, a server for receiving and analyzing the data, an emotion engine for analyzing the user's emotional state and adjusting the in-car environment, and a smartphone application for the user to monitor and adjust the system in real time.

[0838] The server is the heart of the present invention and performs the following functions: Receives measurement data (temperature, voltage, current, remaining charge) from the energy storage device sent from the vehicle. The received data is analyzed using machine learning algorithms using Python and TensorFlow. This optimizes energy use by simulating multiple energy consumption scenarios and selecting the optimal method. Based on the optimal energy management method selected, the server then generates and sends specific commands to the vehicle's energy management system. Examples include load balancing, charging and discharging timing, and activating the cooling system. The server also uses a user emotion engine to analyze the user's voice, facial expressions, and physiological data to generate a user profile based on their emotional state.

[0839] The terminal (vehicle side) is responsible for measuring the status of the energy storage device and periodically transmitting this data to a server. Specifically, it is equipped with sensors that measure the temperature, voltage, current, and remaining energy inside the vehicle. The data is transmitted to the server at regular intervals, and the terminal receives and analyzes commands sent from the server. These commands include reducing energy consumption and starting fast charging. Based on the received commands, the terminal then performs real-time operations such as charging and discharging, activating the cooling system, and optimizing energy consumption. The terminal also uses an emotion engine to analyze the user's voice, facial expression, and physiological data to determine their emotional state. Depending on the emotional state, the terminal adjusts the entertainment system and air conditioning system to improve user comfort.

[0840] Users operate a dedicated application on their smartphone. This application, developed using Flutter and React Native, allows them to monitor the status of the vehicle's energy management system in real time. Through the application, users can check their past energy usage history and adjust energy management settings. For example, they can set things like "enable eco mode" or "delay the next charging session." In addition, the application works with an emotion engine to display the user's emotional state in real time and suggests optimal energy management and environmental settings based on their emotional state.

[0841] As a concrete example, consider a case where a user looks tired while in the car on a hot day. At this time, a sensor on the device (in the vehicle) detects a rise in battery temperature and sends that data (e.g., 45°C) to the server. The emotion engine also analyzes the user's facial expression and determines the level of fatigue. The server receives this data and, based on the analysis results, generates commands such as "activate the cooling system," "play relaxing music," and "set the room temperature to a comfortable level." These commands are sent to the device, which then operates the cooling system, adjusts the entertainment system, and sets the air conditioning system in accordance with the commands. The user can then check these adjustments on their smartphone application and confirm that the optimal environmental settings based on their emotional state have been implemented.

[0842] Examples of input prompts for a generative AI model include:

[0843] Please explain the detailed operational flow of the energy management system in a situation where the user looks tired in the car on a hot day. Please explain each step specifically from the perspective of the server, the terminal (in the car), and the user.

[0844] As described above, the present invention can be implemented by integrating various hardware and software in order to achieve both efficient management of the energy storage device and user comfort.

[0845] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0846] Step 1:

[0847] Battery status measurement and data transmission on the terminal (vehicle side)

[0848] The terminal (vehicle side) uses sensors installed inside the vehicle to measure the temperature, voltage, current, and remaining energy of the energy storage device. The measurement data is collected, for example, every 10 minutes. This data is collected in the telematics unit via the vehicle's CAN bus and periodically sent to the server.

[0849] Input: Battery measurement data from in-vehicle sensors (temperature, voltage, current, remaining capacity)

[0850] Data processing or data calculation: Aggregation of measurement data, shaping of time series data

[0851] Output: Transmission of measurement data from the telematics unit to the server

[0852] Step 2:

[0853] Server data reception and analysis

[0854] The server receives measurement data sent from the terminal (vehicle side). After receiving this data, it is stored in a database and an energy usage optimization algorithm is executed. A machine learning algorithm using Python and TensorFlow analyzes the measurement data and calculates the optimal energy management method.

[0855] Input: Measurement data sent from the device (temperature, voltage, current, remaining capacity)

[0856] Data processing or data calculation: receiving data, storing it in a database, and analyzing it with machine learning algorithms

[0857] Output: Calculation results of optimal energy management method

[0858] Step 3:

[0859] Server command generation

[0860] The server generates specific commands based on the analysis results. These commands include, for example, "reduce energy consumption for the next hour," "start rapid charging," and "activate the cooling system." These commands are then sent back to the terminal (vehicle side).

[0861] Input: Calculation result of optimal energy management method

[0862] Data processing or data calculation: Creation of specific commands using command generation logic

[0863] Output: Specific instructions sent to the terminal

[0864] Step 4:

[0865] Terminal (vehicle side) command reception and execution

[0866] The device receives and analyzes instructions sent from the server, and based on the instructions, performs operations in real time, such as charging and discharging the battery, activating the cooling system, and optimizing energy consumption.

[0867] Input: Specific instructions sent by the server

[0868] Data processing or data calculation: parsing commands and executing control logic for battery management systems and cooling systems

[0869] Output: Specific operation (start of charging / discharging, start of cooling system, etc.)

[0870] Step 5:

[0871] Emotion analysis on the device (vehicle side)

[0872] The device uses cameras and microphones inside the vehicle to collect the user's voice, facial expressions, and physiological data, and analyzes them using an emotion engine. Based on the analysis results, the device determines the user's emotional state.

[0873] Input: User voice, facial expressions, physiological data

[0874] Data processing or data calculation: Emotion analysis using image processing software (OpenCV) and voice analysis tool (Praat)

[0875] Output: Determined user's emotional state

[0876] Step 6:

[0877] Terminal (vehicle side) environment adjustment

[0878] Based on the emotion analysis results, the device can adjust the vehicle's entertainment and climate control systems, for example, playing relaxing music and setting the temperature to a comfortable level if the user is tired.

[0879] Input: Emotion analysis results, environmental adjustment instructions from the server

[0880] Data processing or data calculation: Executing control logic for entertainment systems or air conditioning systems

[0881] Output: Controlled in-car environment (playing music, changing climate settings, etc.)

[0882] Step 7:

[0883] Real-time user monitoring and configuration adjustment

[0884] Users can monitor the status of their vehicle's energy management system in real time and check past energy usage history through a smartphone application. They can also adjust energy management settings through the application, such as enabling Eco Mode or delaying the next charging session.

[0885] Input: Status data from the vehicle's energy management system, user configuration change requests

[0886] Data processing or data calculation: Visualization of status data, execution of energy management setting logic

[0887] Output: Real-time monitoring screen, setting change results

[0888] This completes a series of processes, enabling efficient management of the vehicle's energy storage device and providing a comfortable in-vehicle environment that suits the user's emotional state.

[0889] (Application example 2)

[0890] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0891] Vehicle energy management systems are required to improve battery energy efficiency and realize an optimal in-car environment that responds to the user's emotional state. It is also important that real-time battery status monitoring and energy management settings are easy for users to understand and operate intuitively. To solve these issues, energy management based on the user's emotional state is necessary in addition to optimizing energy use.

[0892] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving battery data transmitted from the vehicle and optimizing energy use, means for analyzing the user's emotional state and generating commands based on the emotional state, and means for generating prompt sentences to be input to the generative AI model. This makes it possible to use energy efficiently and provide a comfortable in-vehicle environment based on the user's emotions.

[0893] "Battery measurement data" refers to various indicators such as the temperature, voltage, current, and remaining energy of the battery inside the vehicle.

[0894] "Energy use optimization" refers to the process of planning and implementing efficient energy usage methods based on battery data.

[0895] An "energy management system" is a system that optimally controls and manages various energy systems, including batteries, inside a vehicle.

[0896] The "user's emotional state" refers to the emotions expressed by the user, and is analyzed from voice, facial expressions, physiological data, and the like.

[0897] "Emotion analysis software" is software that analyzes a user's facial expressions and voice data to determine their emotional state.

[0898] "Real-time execution" means that the entire process, from data acquisition to processing to command execution, occurs with almost no delay.

[0899] A "generative AI model" is a model of artificial intelligence that is trained to perform a specific task.

[0900] A "prompt" is an instruction or question that is input into a generative AI model.

[0901] To implement this invention, the system provides a technology for efficiently managing the battery status in a vehicle and optimizing the in-vehicle environment based on the emotional state of the user. The system configuration and processing details are described below.

[0902] System Program Overview

[0903] This system consists of three main elements: a server, a terminal (in the vehicle), and a user.

[0904] Server Processing

[0905] The server is the center of the system and performs the following processes:

[0906] 1. Receiving and analyzing battery data:

[0907] Receives battery measurement data (temperature, voltage, current, remaining energy) sent from the vehicle.

[0908] It analyzes the received battery data and runs energy usage optimization algorithms.

[0909] 2. Optimizing energy use:

[0910] Multiple scenarios are simulated, the results are evaluated, and the optimal energy management method is selected.

[0911] Based on the optimization results, specific instructions are generated and sent to the vehicle's energy management system.

[0912] 3. Emotion data analysis and command generation:

[0913] Emotion analysis software is used to analyze the user's facial expressions and voice to determine their emotional state.

[0914] Generates commands to entertainment and air conditioning systems based on emotional state.

[0915] 4. Prompt generation:

[0916] Generate prompt sentences to input to the generative AI model.

[0917] Terminal (vehicle side) processing

[0918] The terminal is installed in the vehicle and performs the following processes.

[0919] 1. Battery data measurement and transmission:

[0920] Sensors measure the battery's status (temperature, voltage, current, remaining energy) and periodically send the data to a server.

[0921] 2. Receiving and executing orders:

[0922] Receives and analyzes instructions sent from the server.

[0923] Based on the received commands, it adjusts battery charging and discharging, cooling system operation, and entertainment and air conditioning systems in real time.

[0924] User Action

[0925] The user performs the following operations through a dedicated application.

[0926] 1. Battery status monitoring:

[0927] Launch the application and monitor your vehicle's battery status in real time.

[0928] You can check your past energy usage history through the application.

[0929] 2. Adjust Energy Management Settings:

[0930] Adjust energy management settings, such as "Enable Eco Mode" or "Delay next charging session."

[0931] 3. Reflection of emotional state:

[0932] Optimal energy management and environmental settings are suggested based on the user's emotional state.

[0933] Specific examples

[0934] For example, consider a case where a user looks tired in a car on a hot day.

[0935] 1. Terminal (vehicle side) processing:

[0936] Sensors in the vehicle measure the battery temperature and send the data to a server, while emotion analysis software determines the user's level of fatigue.

[0937] 2. Server processing:

[0938] The server analyzes battery data and emotional data and generates commands such as "start the cooling system," "play relaxing music," and "adjust the air conditioning system."

[0939] 3. Terminal processing:

[0940] The vehicle's energy management system regulates the cooling system, entertainment system, and air conditioning system based on commands from the server.

[0941] Prompt Sentence Examples

[0942] "The battery temperature of the autonomous vehicle has reached 45°C. The user's facial expression indicates that they are tired. Please generate optimal commands."

[0943] In this way, the system of the present invention realizes efficient energy utilization and provides a comfortable in-vehicle environment based on the user's emotions.

[0944] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0945] Step 1: Measuring and sending battery data

[0946] The terminal (vehicle side) uses sensors installed inside the vehicle to measure various indicators such as the battery temperature, voltage, current, and remaining energy. The measured data is sent to the server at regular intervals. The input is the measurement data from the sensors, and the output is the battery data sent to the server.

[0947] Step 2: Receiving and analyzing battery data

[0948] The server receives battery data sent from the vehicle. The received data is analyzed and an energy usage optimization algorithm is executed. The input is the battery data sent from the terminal, and the output is the analysis result and the energy management optimization result.

[0949] Step 3: Optimize energy use

[0950] The server simulates multiple scenarios, evaluates the results, and selects the optimal energy management method. Based on the optimization results, it generates and sends specific instructions. The input is the analyzed battery data, and the output is the optimal energy management method and the corresponding instructions.

[0951] Step 4: Collect and analyze emotion data

[0952] The terminal (in the vehicle) uses cameras and microphones inside the vehicle to collect the user's facial expressions and voice. This data is analyzed by emotion analysis software to determine the user's emotional state. The input is the facial expression and voice data collected by the camera and microphone, and the output is the determined emotional state data.

[0953] Step 5: Command generation based on emotional state

[0954] The server receives the emotion analysis results and generates specific commands for the entertainment system and air conditioning system based on the emotional state. These commands are also sent to the energy management system. The input is the emotion analysis results, and the output is adjustment commands for the entertainment system and air conditioning system.

[0955] Step 6: Execute the directive

[0956] The terminal (on the vehicle side) receives commands from the server and adjusts battery charging / discharging, cooling system operation, entertainment system, and air conditioning system in real time. The input is the command from the server, and the output is the execution result of battery management and environmental adjustment.

[0957] Step 7: Monitor your battery status and adjust settings

[0958] Users can monitor the vehicle's battery status in real time through a dedicated application, and can also use the application to adjust energy management settings. The input is the operating data through the application, and the output is the adjusted energy management settings.

[0959] Step 8: Generate a prompt statement

[0960] The server generates a prompt sentence to be input to the generative AI model. This prompt sentence is generated in an appropriate form based on the overall command of the system. The input is the system state and command data, and the output is the generated prompt sentence.

[0961] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0962] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0963] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0964] [Third embodiment]

[0965] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0966] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0967] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0968] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0969] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0970] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0971] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0972] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0973] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0974] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0975] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0976] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0977] The present invention relates to battery systems in vehicles, and in particular to a system for improving energy efficiency and sustainability, which includes technology for monitoring the battery's condition in real time and achieving optimal energy usage.

[0978] Server Processing

[0979] The server is the heart of the present invention and performs the following processes.

[0980] 1. Receives battery measurement data (temperature, voltage, current, remaining charge) sent from the vehicle.

[0981] 2. The received measurement data is analyzed and an energy usage optimization algorithm is run, which simulates multiple scenarios, evaluates the results, and selects the optimal energy management method.

[0982] 3. Based on this selection, specific instructions are generated and sent to the vehicle's energy management system, such as load balancing, charging / discharging timing, and cooling system adjustments.

[0983] Terminal (vehicle side) processing

[0984] The terminal is installed in the vehicle and performs the following processing.

[0985] 1. Measure the battery status (temperature, voltage, current, remaining capacity) through sensors and send the data to the server at regular intervals.

[0986] 2. Receive and analyze commands sent from the server, such as "reduce energy consumption for the next hour" or "start fast charging."

[0987] 3. Based on the received commands, the system performs tasks such as charging and discharging the battery, operating the cooling system, and optimizing energy consumption in real time.

[0988] User Action

[0989] The user performs the following operations through a dedicated application.

[0990] 1. Launch the application and monitor your vehicle's battery status in real time.

[0991] 2. You can check your energy usage history through the application, such as daily energy consumption and charging / discharging schedules.

[0992] 3. Energy management settings can be adjusted through the application, such as "enable eco mode" or "delay the next charging session," allowing users to customize energy management to suit their lifestyle.

[0993] Specific examples

[0994] For example, consider the case where a vehicle's battery temperature rises on a hot day.

[0995] Terminal (vehicle side) processing: The vehicle's sensor detects a rise in battery temperature and sends that data (e.g., 45°C) to the server.

[0996] Server processing: The server receives this data and uses an algorithm to calculate the optimal course of action, resulting in a command to "activate the cooling system to lower the battery temperature."

[0997] Terminal processing: Based on the received command, the vehicle's energy management system activates the cooling system to maintain the battery temperature within an appropriate range.

[0998] User Action: The user can view this information in real time in the application. For example, the user can see that the battery temperature has dropped from 45°C to 25°C.

[0999] Through this process, the system of the present invention significantly improves battery efficiency and sustainability, extending vehicle range and battery life.

[1000] The processing flow will be explained below.

[1001] Server Processing

[1002] Step 1:

[1003] The server waits for battery measurement data to be sent from the vehicle.

[1004] Step 2:

[1005] The server receives battery measurement data sent from the vehicle, including temperature, voltage, current, and remaining energy.

[1006] Step 3:

[1007] The server analyzes the received measurement data, which includes outlier detection and data normalization.

[1008] Step 4:

[1009] The server runs an energy usage optimization algorithm based on the analyzed data, simulating multiple scenarios and evaluating the results.

[1010] Step 5:

[1011] The server selects the optimal energy management strategy and generates specific instructions based on it, including load balancing, charging and discharging timing, and cooling system adjustments.

[1012] Step 6:

[1013] The server transmits the generated command to the vehicle (terminal).

[1014] Terminal (vehicle side) processing

[1015] Step 1:

[1016] The device activates sensors to measure the battery's temperature, voltage, current, and remaining energy.

[1017] Step 2:

[1018] The terminal collects the measurement data from the sensors and assembles them into a single data packet.

[1019] Step 3:

[1020] The terminal transmits the measurement data to the server at regular intervals.

[1021] Step 4:

[1022] The terminal waits for a command sent from the server.

[1023] Step 5:

[1024] The terminal analyzes the command received from the server, including checking the type of command and how to execute it.

[1025] Step 6:

[1026] Based on the received instructions, the device charges and discharges the battery, activates the cooling system, and optimizes energy consumption.

[1027] User Action

[1028] Step 1:

[1029] The user starts a dedicated application.

[1030] Step 2:

[1031] The user requests data from the server to check the current battery status from the application.

[1032] Step 3:

[1033] The user monitors the battery status displayed in the application in real time.

[1034] Step 4:

[1035] Through the application, users can check their energy usage history, including energy consumption and charging / discharging schedules.

[1036] Step 5:

[1037] The user changes the energy management settings through the application.

[1038] Step 6:

[1039] Any changes to the user's settings are sent to the server, which then readjusts the energy management algorithms based on the settings.

[1040] This allows users to monitor battery status in real time and adjust energy management settings to suit their lifestyle.

[1041] Example 1

[1042] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1043] The aim of this invention is to improve the energy efficiency and sustainability of in-vehicle battery systems. However, conventional systems do not adequately monitor battery status in real time and perform data analysis and optimization algorithms to optimize energy usage. As a result, efficient battery use and extended battery life have been challenges.

[1044] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1045] In this invention, the server includes means for receiving measurement data and storing it in a database, means for analyzing the stored measurement data, and means for executing an energy usage optimization algorithm based on the analysis results, thereby enabling real-time monitoring of the battery status, selecting an optimal energy management method, and generating and transmitting commands, thereby enabling efficient use of the battery and extending its lifespan.

[1046] A "vehicle" is a machine that has a battery inside and moves by consuming energy.

[1047] A "battery" is a device that converts chemical energy into electrical energy and provides power for a period of time.

[1048] "Measurement data" is numerical data that indicates information about the state of the battery, and specifically includes temperature, voltage, current, and remaining energy.

[1049] A "server" is a computer system that receives, stores, analyzes, and processes data as needed.

[1050] A "database" is an information system for efficiently storing and managing large amounts of data.

[1051] "Analysis" is the act of evaluating and understanding the state and characteristics of an object based on collected data.

[1052] An "optimization algorithm" is a computational procedure for maximizing or minimizing the performance of a goal while taking into account multiple criteria.

[1053] A "command" is a specific operation instruction sent from the server to the terminal.

[1054] An "energy management system" is a system for managing and optimizing the energy consumption of batteries and vehicles.

[1055] "Real-time" refers to the immediate reflection of current status and behavior.

[1056] The present invention relates to a battery system in a vehicle, and in particular to a system for improving energy efficiency and sustainability, including technology for monitoring the state of the vehicle battery in real time to achieve optimal energy usage.

[1057] Server Processing

[1058] The server is the heart of the invention, receiving battery measurement data (temperature, voltage, current, remaining charge) sent from the vehicle and storing it in a database. The server uses MySQL or PostgreSQL as its database management system (DBMS). The stored data is analyzed and an energy usage optimization algorithm is executed. This algorithm simulates multiple scenarios and evaluates the results to select the optimal energy management method. Analysis tools such as Python's Pandas and NumPy are used for the analysis. Based on the results, specific commands (e.g., load balancing, charging / discharging timing, and cooling system adjustment) are generated and sent to the vehicle's energy management system.

[1059] Terminal (vehicle side) processing

[1060] The terminal is installed inside the vehicle and measures the battery condition through sensors, periodically sending the data to the server. A communications library is used to send the data. The terminal also receives and analyzes commands sent from the server. This analysis includes parsing the data and judging various conditions. Based on the received commands, the terminal performs real-time operations such as charging and discharging the battery, operating the cooling system, and optimizing energy consumption.

[1061] User Action

[1062] Users can monitor their vehicle's battery status in real time through a dedicated application. This application runs on a mobile device and provides the vehicle's battery status. Users can also check their past energy usage history through the application. Specifically, this includes functions to display daily energy consumption and charging / discharging schedules. In addition, they can adjust energy management settings. For example, they can enable Eco Mode or delay the next charging session.

[1063] Specific examples

[1064] For example, consider the case where a vehicle's battery temperature rises on a hot day. The device's sensor detects the rise in battery temperature and sends that data (for example, 45°C) to the server. The server receives this data, uses an algorithm to calculate the optimal response, and generates a command to "activate the cooling system to lower the battery temperature." Based on the received command, the vehicle's energy management system activates the cooling system to maintain the battery temperature within an appropriate range. The user can check this information in real time in the application. For example, they can see that the battery temperature has dropped from 45°C to 25°C.

[1065] Prompt Sentence Examples

[1066] Example prompts to input to a generative AI model:

[1067] Please write a description of the functionality of a vehicle's battery management system, including how sensors measure battery status and send that data to a server for analysis and optimization. Also, please include functionality that allows users to monitor battery status and adjust energy management through an application.

[1068] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1069] Step 1:

[1070] Server data reception

[1071] Input: Battery measurement data sent from the vehicle (temperature, voltage, current, remaining energy)

[1072] Processing: The server receives this data via HTTP communication. Specifically, the communication module parses and validates the received data.

[1073] Output: Measurement data in a format suitable for analysis

[1074] Step 2:

[1075] Server database storage

[1076] Input: Measurement data in a format suitable for analysis

[1077] Processing: The server stores the received data in a database and executes SQL queries using MySQL or PostgreSQL as the database management system (DBMS).

[1078] Output: Measurement data stored in a database

[1079] Step 3:

[1080] Server data analysis

[1081] Input: Measurement data stored in the database

[1082] Processing: The server uses Python's Pandas and NumPy to analyze the stored data, including calculating the mean, standard deviation, and outlier detection.

[1083] Output: Parsed battery data

[1084] Step 4:

[1085] Optimization algorithm execution on the server

[1086] Input: Parsed battery data

[1087] Processing: The server runs an energy usage optimization algorithm based on the analysis results. This algorithm uses Gurobi and SciPy to simulate multiple scenarios and select the optimal energy management method.

[1088] Output: Optimized energy management methods and specific directives

[1089] Step 5:

[1090] Server command generation and transmission

[1091] Input: Optimized energy management methods and specific directives

[1092] Processing: The server formats the command in JSON format and sends it to the vehicle's terminal via HTTP communication.

[1093] Output: Commands sent to the vehicle's terminal

[1094] Step 6:

[1095] Device sensor data measurement

[1096] Input: None

[1097] Processing: The terminal measures the battery status (temperature, voltage, current, remaining energy) using sensors in the vehicle, including temperature, voltage, and current sensors.

[1098] Output: Measured battery data

[1099] Step 7:

[1100] Data transmission from the device

[1101] Input: Measured battery data

[1102] Processing: The device sends the data to the server by performing an HTTP POST request using a communication library.

[1103] Output: Battery data sent to the server

[1104] Step 8:

[1105] Terminal command reception and analysis

[1106] Input: Command sent from the server

[1107] Processing: The device receives the command, analyzes the command content, parses the JSON format data, and makes a decision based on various conditions.

[1108] Output: Parsed command content

[1109] Step 9:

[1110] Terminal command execution

[1111] Input: Parsed command content

[1112] Processing: Based on the received instructions, the device will charge and discharge the battery, activate the cooling system, and optimize energy consumption in real time, such as activating the cooling system and adjusting the charging schedule.

[1113] Output: Energy management operations performed

[1114] Step 10:

[1115] Real-time user monitoring

[1116] Input: Battery data

[1117] Processing: The user launches a dedicated application, which retrieves the latest battery data from the server and displays it.

[1118] Output: Real-time updated battery status

[1119] Step 11:

[1120] Check user's past data

[1121] Input: Battery usage history for a user-specified period

[1122] Processing: The application retrieves historical data from the server and displays it to the user in the form of graphs and lists.

[1123] Output: Display of past energy usage history

[1124] Step 12:

[1125] Adjusting User Settings

[1126] Input: Energy management settings changed by the user

[1127] Processing: The user adjusts the energy management settings through the application's settings screen and sends the settings to the server.

[1128] Output: Updated Energy Management Settings

[1129] (Application example 1)

[1130] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1131] Conventional vehicle battery systems lack the technology to monitor battery status in real time and perform optimal energy management. They also lack sufficient means to provide users with timely energy management information, such as notifications of abnormal values ​​or displaying past usage history. Another issue is that it is difficult for users to adjust energy management settings via smart devices.

[1132] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1133] In this invention, the server includes a means for receiving battery measurement data and optimizing energy use, a means for sending commands to the vehicle's energy management system based on the energy use optimization, a means for displaying battery measurement data on the smart device in real time, a means for notifying of abnormal values, a means for presenting the battery energy management status as alerts or commands via the smart device, and a means for retrieving and displaying past battery usage history from a database. This enables optimal energy management by monitoring the battery status in real time and immediately notifying the user if an abnormality occurs. Furthermore, the user can easily check past usage history and adjust energy management settings via the smart device.

[1134] "Battery temperature" refers to the degree of thermal energy currently held by the battery in the vehicle.

[1135] "Voltage" refers to the potential difference produced by a vehicle's battery.

[1136] "Current" is a quantity that indicates the flow of electrons from a battery in a vehicle.

[1137] "Remaining energy" is the total amount of energy currently remaining in the vehicle's battery.

[1138] "Measurement data" refers to information about the battery's temperature, voltage, current, and remaining energy.

[1139] The "transmission means" is a communication means for sending the measurement data to the server.

[1140] The "optimization means" is a means for executing an algorithm to improve the efficiency of energy use based on the measurement data.

[1141] A "command" is an operational instruction sent to the energy management system.

[1142] A "smart device" is a multi-function device that has the ability to connect to the Internet and run applications.

[1143] The "real-time display means" is a means for displaying battery measurement data on a smart device in real time.

[1144] The "abnormal value notification means" is a means for notifying when an abnormality in the battery state is detected.

[1145] The "energy management status presentation means" is a means for presenting the optimization status of energy usage to the user as alerts or instructions via a smart device.

[1146] "Past usage history" refers to data on the battery's past voltage, current, temperature, and remaining energy.

[1147] A "database" is an information storage means for recording and saving past usage history.

[1148] This invention relates to a battery system for autonomous vehicles, and in particular to a system for improving energy efficiency and sustainability. The system measures the temperature, voltage, current, and remaining energy of the vehicle battery in real time, enabling optimal energy management.

[1149] Server Processing

[1150] The server is the core of the present invention and performs the following processes: First, it receives battery measurement data (temperature, voltage, current, remaining charge) sent from the vehicle. It analyzes this data and runs an energy usage optimization algorithm. The hardware and software used include cloud servers (e.g., AWS Lambda, Google Cloud Functions). The algorithm simulates multiple scenarios, evaluates the results, and selects the optimal energy management method. Finally, it generates and sends commands to the vehicle's energy management system based on the optimization results.

[1151] Terminal (vehicle side) processing

[1152] The terminal is installed inside the vehicle and measures the battery's status (temperature, voltage, current, remaining charge) through sensors, sending the data to a server at regular intervals. This data is displayed in real time mainly through smart devices. It also receives commands sent from the server and, based on those commands, performs tasks such as charging and discharging the battery, operating the cooling system, and optimizing energy consumption. The hardware used consists of a sensor system and communication module inside the vehicle.

[1153] User Action

[1154] Users use a dedicated smart device (e.g., smart glasses or a smartphone) to perform the following processes. First, the smart device has a function to display battery measurement data in real time. If an abnormal value is detected, an alert will be sent. In addition, past battery usage history can be retrieved from a database and easily checked through the smart device. Furthermore, users can adjust energy management settings through the smart device, which allows energy management to be optimized to suit their individual usage conditions.

[1155] Specific examples

[1156] If the battery temperature rises on a hot day, the following process occurs: The device's sensor detects a rise in battery temperature (e.g., 50°C) and sends the data to the server. The server receives this data and generates a command to activate the cooling system. This command activates the vehicle's cooling system, maintaining the battery temperature within an appropriate range (e.g., 25°C to 45°C). The user can check the change in battery temperature in real time through the smart glasses. Furthermore, if an abnormal value is detected, a prompt message will be displayed: "The current battery temperature is 50°C. Please activate the cooling system."

[1157] This allows the system of the present invention to significantly improve battery efficiency and sustainability, extending vehicle range and battery life.

[1158] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1159] Specific explanation of processing steps

[1160] Step 1: Data measurement using the terminal (vehicle side)

[1161] Sensors installed inside the vehicle measure the battery's temperature, voltage, current and remaining energy.

[1162] Input: Battery physical status (temperature, voltage, current, remaining energy)

[1163] Data processing: Each sensor converts analog data into digital form

[1164] Output: Battery status information as digital data

[1165] Step 2: Send data by device

[1166] The measured digital data of the battery is sent to the server at regular intervals.

[1167] Input: Digital data (temperature, voltage, current, remaining energy)

[1168] Data processing: Packetizing and encoding data

[1169] Output: Sent to the server as a communication packet

[1170] Step 3: Data reception and analysis by the server

[1171] The server analyzes the received battery data and runs an energy usage optimization algorithm.

[1172] Input: Battery data sent from the vehicle

[1173] Data computation: running energy optimization algorithms, simulating multiple scenarios

[1174] Output: Selection of optimal energy management method

[1175] Step 4: Optimization instructions generated by the server

[1176] Based on the optimal energy management method, a command is generated to be sent to the vehicle's energy management system.

[1177] Input: Result of optimal energy management method selection

[1178] Data processing: Command data generation and encoding

[1179] Output: Sends operation commands to the vehicle

[1180] Step 5: Receive and execute commands on the terminal (vehicle side)

[1181] The terminal on the vehicle receives commands sent from the server and operates the battery charging / discharging and cooling system based on those commands.

[1182] Input: Command data from the server

[1183] Data processing: Decoding and interpretation of command data

[1184] Output: Performing battery management actions (e.g., activating the cooling system)

[1185] Step 6: User monitors battery status

[1186] Users can use their smart devices to monitor battery status in real time.

[1187] Input: Battery data from the vehicle, command data from the server

[1188] Data calculation: Data display, abnormal value notification

[1189] Output: Visual information on smart devices

[1190] Step 7: User checks past historical data

[1191] Users can check past battery usage history via their smart device.

[1192] Input: Previously recorded battery data (retrieved from database)

[1193] Data calculation: Data search and display

[1194] Output: Display of analysis results

[1195] Step 8: User adjusts energy management settings

[1196] Users adjust energy management settings through their smart devices.

[1197] Input: Configuration data entered by the user

[1198] Data calculation: Processing of setting data, sending to server

[1199] Output: Applying adjusted energy management settings

[1200] Specific working example:

[1201] Example 1:

[1202] Step 1: A sensor inside the vehicle measures the battery temperature of 50°C and converts it into digital data.

[1203] Step 2: Send the converted digital data to the server.

[1204] Step 3: The server analyzes the received data and determines whether the cooling system needs to be activated.

[1205] Step 4: The server generates a "start cooling system" command and sends it to the vehicle.

[1206] Step 5: The vehicle's terminal receives the command and activates the cooling system.

[1207] Step 6: The user confirms through their smart device that the temperature has dropped from 50°C to 25°C.

[1208] Step 7: The user checks the battery temperature history on their smart device.

[1209] Step 8: The user adjusts the energy management settings to "Eco Mode."

[1210] Example 2:

[1211] The prompt text "The current battery temperature is 50°C. Please activate the cooling system." will be displayed on the smart device.

[1212] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1213] The present invention relates to an energy management system that combines a vehicle's battery system with a user's emotion engine, and in particular improves energy efficiency, enhances sustainability, and realizes energy management and in-vehicle environment optimization based on the user's emotional state.

[1214] Server Processing

[1215] The server is the heart of the present invention and performs the following processes.

[1216] 1. Receives battery measurement data (temperature, voltage, current, remaining charge) sent from the vehicle.

[1217] 2. The received measurement data is analyzed and an energy usage optimization algorithm is run, which simulates multiple scenarios, evaluates the results, and selects the optimal energy management method.

[1218] 3. Based on this, it generates and sends specific instructions to the vehicle's energy management system, such as load balancing, charging and discharging timing, and adjusting the cooling system.

[1219] 4. The user emotion engine is linked to the database to generate a user profile based on the emotional state.

[1220] Terminal (vehicle side) processing

[1221] The terminal is installed in the vehicle and performs the following processing.

[1222] 1. Measure the battery status (temperature, voltage, current, remaining capacity) through sensors and send the data to the server at regular intervals.

[1223] 2. Receive and analyze commands sent from the server, such as "reduce energy consumption for the next hour" or "start fast charging."

[1224] 3. Based on the received commands, the system performs tasks such as charging and discharging the battery, operating the cooling system, and optimizing energy consumption in real time.

[1225] 4. Using an emotion engine, the user's voice, facial expressions, and physiological data are analyzed to determine their emotional state.

[1226] 5. Adjust the entertainment and climate control systems in your vehicle based on your emotional state.

[1227] User Action

[1228] The user performs the following operations through a dedicated application.

[1229] 1. Launch the application and monitor your vehicle's battery status in real time.

[1230] 2. You can check your energy usage history through the application, such as daily energy consumption and charging / discharging schedules.

[1231] 3. Energy management settings can be adjusted through the application, such as "enable eco mode" or "delay the next charging session," allowing users to customize energy management to suit their lifestyle.

[1232] 4. The application works in conjunction with the emotion engine to display the user's emotional state in real time and suggest optimal energy management and environmental settings based on the user's emotional state.

[1233] Specific examples

[1234] For example, consider a case where a user looks tired in a car on a hot day.

[1235] Processing on the terminal (vehicle side): The vehicle's sensor detects a rise in battery temperature and sends that data (e.g., 45°C) to the server. The emotion engine also analyzes the user's facial expressions to determine their level of fatigue.

[1236] Server processing: The server receives battery data and user emotion data and uses an algorithm to calculate the optimal response, generating commands such as "activate the cooling system to lower the battery temperature," "play relaxing music on the entertainment system," and "adjust the heating and cooling system to maintain a comfortable room temperature."

[1237] Terminal processing: The vehicle's energy management system operates the cooling system based on commands from the server to maintain the battery temperature within an appropriate range, as well as regulating the entertainment system and air conditioning system.

[1238] User Action: The user can see these adjustments in real time in the application, ensuring optimal preferences are set based on their emotions.

[1239] Through this process, the system of the present invention not only significantly improves battery efficiency and sustainability, but also provides a comfortable in-car environment that responds to the user's emotional state.

[1240] The processing flow will be explained below.

[1241] Server Processing

[1242] Step 1:

[1243] The server waits for battery measurement data to be sent from the vehicle.

[1244] Step 2:

[1245] The server receives battery measurement data sent from the vehicle, including temperature, voltage, current, and remaining energy.

[1246] Step 3:

[1247] The server analyzes the received measurement data, including detecting outliers and normalizing the data.

[1248] Step 4:

[1249] The server runs an energy usage optimization algorithm based on the analyzed data, simulating multiple scenarios and evaluating the results.

[1250] Step 5:

[1251] The server selects the optimal energy management strategy and generates specific instructions based on it, including load balancing, charging and discharging timing, and cooling system adjustments.

[1252] Step 6:

[1253] The server transmits the generated command to the vehicle (terminal).

[1254] Step 7:

[1255] The server interfaces the user's emotion engine with the database to update the user profile based on the emotional state.

[1256] Terminal (vehicle side) processing

[1257] Step 1:

[1258] The device activates sensors to measure the battery's temperature, voltage, current, and remaining energy.

[1259] Step 2:

[1260] The terminal collects the measurement data from the sensors and assembles them into a single data packet.

[1261] Step 3:

[1262] The terminal transmits the measurement data to the server at regular intervals.

[1263] Step 4:

[1264] The terminal waits for a command sent from the server.

[1265] Step 5:

[1266] The terminal analyzes the command received from the server, including checking the type of command and how to execute it.

[1267] Step 6:

[1268] Based on the received instructions, the device charges and discharges the battery, activates the cooling system, and optimizes energy consumption.

[1269] Step 7:

[1270] The device uses an emotion engine to analyze the user's voice, facial expressions, and physiological data to determine their emotional state.

[1271] Step 8:

[1272] The terminal sends commands to the system to adjust the entertainment system and air conditioning system in the vehicle depending on the emotional state.

[1273] User Action

[1274] Step 1:

[1275] The user starts a dedicated application.

[1276] Step 2:

[1277] The user requests data from the server to check the current battery status from the application.

[1278] Step 3:

[1279] The user monitors the battery status displayed in the application in real time.

[1280] Step 4:

[1281] Through the application, users can check their energy usage history, including energy consumption and charging / discharging schedules.

[1282] Step 5:

[1283] The user changes the energy management settings through the application.

[1284] Step 6:

[1285] Any changes to the user's settings are sent to the server, which then readjusts the energy management algorithms based on the settings.

[1286] Step 7:

[1287] Users can see the results of the emotion engine in real time through the application.

[1288] Step 8:

[1289] The user can check the application for suggestions for optimal energy management and environmental settings based on their emotional state and make adjustments as needed.

[1290] This allows users to monitor battery status in real time and adjust energy management settings to suit their lifestyle, while the emotion engine provides adaptive environmental adjustments to provide a more comfortable driving experience.

[1291] Example 2

[1292] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1293] In modern vehicles, it is difficult to simultaneously optimize energy management and user comfort. In particular, efficient management of energy storage devices and adjustment of the in-vehicle environment based on the user's emotional state are required, but a system that controls these in an integrated manner is lacking. This leads to issues such as reduced energy efficiency and reduced user comfort.

[1294] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1295] In this invention, the server includes means for measuring the temperature, voltage, current, and remaining energy of an energy storage device in the vehicle, means for periodically transmitting measurement data from the energy storage device, means for receiving the measurement data from the energy storage device and optimizing energy use, means for simulating multiple energy consumption scenarios and evaluating the results to select an optimal energy management method, and means for detecting the emotional state of the user and adjusting environmental settings in the vehicle based on the emotional state, thereby enabling both improved energy efficiency and user comfort.

[1296] An "energy storage device" is a device for storing electricity within a vehicle, and mainly refers to batteries and capacitors.

[1297] "Measurement data" refers to data that represents physical quantities such as the temperature, voltage, current, and remaining energy of the energy storage device.

[1298] "Energy use optimization" refers to calculating and adjusting efficient energy management and usage methods based on received measurement data.

[1299] A "command" is a specific instruction sent from the server to the terminal to prompt changes to the settings of the energy storage device or the in-vehicle environment.

[1300] "Energy management system" means a system for efficiently managing the supply and use of energy in a vehicle.

[1301] "Emotional state" refers to a psychological state inferred from a user's voice, facial expression, and physiological data.

[1302] "Environmental settings" refers to settings that adjust the in-car entertainment system, air conditioning system, etc.

[1303] An "entertainment system" is a system that provides entertainment such as music playback, video playback, and games in a vehicle.

[1304] An "air conditioning system" is a system that adjusts the temperature and humidity inside a vehicle to provide a comfortable environment.

[1305] "Real-time" means that the system processes data immediately and provides information or takes action nearly instantaneously in real time.

[1306] To implement this invention, the following hardware and software are required: a sensor for measuring the status of an energy storage device installed in a vehicle, a communication module for periodically transmitting data, a server for receiving and analyzing the data, an emotion engine for analyzing the user's emotional state and adjusting the in-car environment, and a smartphone application for the user to monitor and adjust the system in real time.

[1307] The server is the heart of the present invention and performs the following functions: Receives measurement data (temperature, voltage, current, remaining charge) from the energy storage device sent from the vehicle. The received data is analyzed using machine learning algorithms using Python and TensorFlow. This optimizes energy use by simulating multiple energy consumption scenarios and selecting the optimal method. Based on the optimal energy management method selected, the server then generates and sends specific commands to the vehicle's energy management system. Examples include load balancing, charging and discharging timing, and activating the cooling system. The server also uses a user emotion engine to analyze the user's voice, facial expressions, and physiological data to generate a user profile based on their emotional state.

[1308] The terminal (vehicle side) is responsible for measuring the status of the energy storage device and periodically transmitting this data to a server. Specifically, it is equipped with sensors that measure the temperature, voltage, current, and remaining energy inside the vehicle. The data is transmitted to the server at regular intervals, and the terminal receives and analyzes commands sent from the server. These commands include reducing energy consumption and starting fast charging. Based on the received commands, the terminal then performs real-time operations such as charging and discharging, activating the cooling system, and optimizing energy consumption. The terminal also uses an emotion engine to analyze the user's voice, facial expression, and physiological data to determine their emotional state. Depending on the emotional state, the terminal adjusts the entertainment system and air conditioning system to improve user comfort.

[1309] Users operate a dedicated application on their smartphone. This application, developed using Flutter and React Native, allows them to monitor the status of the vehicle's energy management system in real time. Through the application, users can check their past energy usage history and adjust energy management settings. For example, they can set things like "enable eco mode" or "delay the next charging session." In addition, the application works with an emotion engine to display the user's emotional state in real time and suggests optimal energy management and environmental settings based on their emotional state.

[1310] As a concrete example, consider a case where a user looks tired while in the car on a hot day. At this time, a sensor on the device (in the vehicle) detects a rise in battery temperature and sends that data (e.g., 45°C) to the server. The emotion engine also analyzes the user's facial expression and determines the level of fatigue. The server receives this data and, based on the analysis results, generates commands such as "activate the cooling system," "play relaxing music," and "set the room temperature to a comfortable level." These commands are sent to the device, which then operates the cooling system, adjusts the entertainment system, and sets the air conditioning system in accordance with the commands. The user can then check these adjustments on their smartphone application and confirm that the optimal environmental settings based on their emotional state have been implemented.

[1311] Examples of input prompts for a generative AI model include:

[1312] Please explain the detailed operational flow of the energy management system in a situation where the user looks tired in the car on a hot day. Please explain each step specifically from the perspective of the server, the terminal (in the car), and the user.

[1313] As described above, the present invention can be implemented by integrating various hardware and software in order to achieve both efficient management of the energy storage device and user comfort.

[1314] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1315] Step 1:

[1316] Battery status measurement and data transmission on the terminal (vehicle side)

[1317] The terminal (vehicle side) uses sensors installed inside the vehicle to measure the temperature, voltage, current, and remaining energy of the energy storage device. The measurement data is collected, for example, every 10 minutes. This data is collected in the telematics unit via the vehicle's CAN bus and periodically sent to the server.

[1318] Input: Battery measurement data from in-vehicle sensors (temperature, voltage, current, remaining capacity)

[1319] Data processing or data calculation: Aggregation of measurement data, shaping of time series data

[1320] Output: Transmission of measurement data from the telematics unit to the server

[1321] Step 2:

[1322] Server data reception and analysis

[1323] The server receives measurement data sent from the terminal (vehicle side). After receiving this data, it is stored in a database and an energy usage optimization algorithm is executed. A machine learning algorithm using Python and TensorFlow analyzes the measurement data and calculates the optimal energy management method.

[1324] Input: Measurement data sent from the device (temperature, voltage, current, remaining capacity)

[1325] Data processing or data calculation: receiving data, storing it in a database, and analyzing it with machine learning algorithms

[1326] Output: Calculation results of optimal energy management method

[1327] Step 3:

[1328] Server command generation

[1329] The server generates specific commands based on the analysis results. These commands include, for example, "reduce energy consumption for the next hour," "start rapid charging," and "activate the cooling system." These commands are then sent back to the terminal (vehicle side).

[1330] Input: Calculation result of optimal energy management method

[1331] Data processing or data calculation: Creation of specific commands using command generation logic

[1332] Output: Specific instructions sent to the terminal

[1333] Step 4:

[1334] Terminal (vehicle side) command reception and execution

[1335] The device receives and analyzes instructions sent from the server, and based on the instructions, performs operations in real time, such as charging and discharging the battery, activating the cooling system, and optimizing energy consumption.

[1336] Input: Specific instructions sent by the server

[1337] Data processing or data calculation: parsing commands and executing control logic for battery management systems and cooling systems

[1338] Output: Specific operation (start of charging / discharging, start of cooling system, etc.)

[1339] Step 5:

[1340] Emotion analysis on the device (vehicle side)

[1341] The device uses cameras and microphones inside the vehicle to collect the user's voice, facial expressions, and physiological data, and analyzes them using an emotion engine. Based on the analysis results, the device determines the user's emotional state.

[1342] Input: User voice, facial expressions, physiological data

[1343] Data processing or data calculation: Emotion analysis using image processing software (OpenCV) and voice analysis tool (Praat)

[1344] Output: Determined user's emotional state

[1345] Step 6:

[1346] Terminal (vehicle side) environment adjustment

[1347] Based on the emotion analysis results, the device can adjust the vehicle's entertainment and climate control systems, for example, playing relaxing music and setting the temperature to a comfortable level if the user is tired.

[1348] Input: Emotion analysis results, environmental adjustment instructions from the server

[1349] Data processing or data calculation: Executing control logic for entertainment systems or air conditioning systems

[1350] Output: Controlled in-car environment (playing music, changing climate settings, etc.)

[1351] Step 7:

[1352] Real-time user monitoring and configuration adjustment

[1353] Users can monitor the status of their vehicle's energy management system in real time and check past energy usage history through a smartphone application. They can also adjust energy management settings through the application, such as enabling Eco Mode or delaying the next charging session.

[1354] Input: Status data from the vehicle's energy management system, user configuration change requests

[1355] Data processing or data calculation: Visualization of status data, execution of energy management setting logic

[1356] Output: Real-time monitoring screen, setting change results

[1357] This completes a series of processes, enabling efficient management of the vehicle's energy storage device and providing a comfortable in-vehicle environment that suits the user's emotional state.

[1358] (Application example 2)

[1359] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1360] Vehicle energy management systems are required to improve battery energy efficiency and realize an optimal in-car environment that responds to the user's emotional state. It is also important that real-time battery status monitoring and energy management settings are easy for users to understand and operate intuitively. To solve these issues, energy management based on the user's emotional state is necessary in addition to optimizing energy use.

[1361] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving battery data transmitted from the vehicle and optimizing energy use, means for analyzing the user's emotional state and generating commands based on the emotional state, and means for generating prompt sentences to be input to the generative AI model. This makes it possible to use energy efficiently and provide a comfortable in-vehicle environment based on the user's emotions.

[1362] "Battery measurement data" refers to various indicators such as the temperature, voltage, current, and remaining energy of the battery inside the vehicle.

[1363] "Energy use optimization" refers to the process of planning and implementing efficient energy usage methods based on battery data.

[1364] An "energy management system" is a system that optimally controls and manages various energy systems, including batteries, inside a vehicle.

[1365] The "user's emotional state" refers to the emotions expressed by the user, and is analyzed from voice, facial expressions, physiological data, and the like.

[1366] "Emotion analysis software" is software that analyzes a user's facial expressions and voice data to determine their emotional state.

[1367] "Real-time execution" means that the entire process, from data acquisition to processing to command execution, occurs with almost no delay.

[1368] A "generative AI model" is a model of artificial intelligence that is trained to perform a specific task.

[1369] A "prompt" is an instruction or question that is input into a generative AI model.

[1370] To implement this invention, the system provides a technology for efficiently managing the battery status in a vehicle and optimizing the in-vehicle environment based on the emotional state of the user. The system configuration and processing details are described below.

[1371] System Program Overview

[1372] This system consists of three main elements: a server, a terminal (in the vehicle), and a user.

[1373] Server Processing

[1374] The server is the center of the system and performs the following processes:

[1375] 1. Receiving and analyzing battery data:

[1376] Receives battery measurement data (temperature, voltage, current, remaining energy) sent from the vehicle.

[1377] It analyzes the received battery data and runs energy usage optimization algorithms.

[1378] 2. Optimizing energy use:

[1379] Multiple scenarios are simulated, the results are evaluated, and the optimal energy management method is selected.

[1380] Based on the optimization results, specific instructions are generated and sent to the vehicle's energy management system.

[1381] 3. Emotion data analysis and command generation:

[1382] Emotion analysis software is used to analyze the user's facial expressions and voice to determine their emotional state.

[1383] Generates commands to entertainment and air conditioning systems based on emotional state.

[1384] 4. Prompt generation:

[1385] Generate prompt sentences to input to the generative AI model.

[1386] Terminal (vehicle side) processing

[1387] The terminal is installed in the vehicle and performs the following processes.

[1388] 1. Battery data measurement and transmission:

[1389] Sensors measure the battery's status (temperature, voltage, current, remaining energy) and periodically send the data to a server.

[1390] 2. Receiving and executing orders:

[1391] Receives and analyzes instructions sent from the server.

[1392] Based on the received commands, it adjusts battery charging and discharging, cooling system operation, and entertainment and air conditioning systems in real time.

[1393] User Action

[1394] The user performs the following operations through a dedicated application.

[1395] 1. Battery status monitoring:

[1396] Launch the application and monitor your vehicle's battery status in real time.

[1397] You can check your past energy usage history through the application.

[1398] 2. Adjust Energy Management Settings:

[1399] Adjust energy management settings, such as "Enable Eco Mode" or "Delay next charging session."

[1400] 3. Reflection of emotional state:

[1401] Optimal energy management and environmental settings are suggested based on the user's emotional state.

[1402] Specific examples

[1403] For example, consider a case where a user looks tired in a car on a hot day.

[1404] 1. Terminal (vehicle side) processing:

[1405] Sensors in the vehicle measure the battery temperature and send the data to a server, while emotion analysis software determines the user's level of fatigue.

[1406] 2. Server processing:

[1407] The server analyzes battery data and emotional data and generates commands such as "start the cooling system," "play relaxing music," and "adjust the air conditioning system."

[1408] 3. Terminal processing:

[1409] The vehicle's energy management system regulates the cooling system, entertainment system, and air conditioning system based on commands from the server.

[1410] Prompt Sentence Examples

[1411] "The battery temperature of the autonomous vehicle has reached 45°C. The user's facial expression indicates that they are tired. Please generate optimal commands."

[1412] In this way, the system of the present invention realizes efficient energy utilization and provides a comfortable in-vehicle environment based on the user's emotions.

[1413] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1414] Step 1: Measuring and sending battery data

[1415] The terminal (vehicle side) uses sensors installed inside the vehicle to measure various indicators such as the battery temperature, voltage, current, and remaining energy. The measured data is sent to the server at regular intervals. The input is the measurement data from the sensors, and the output is the battery data sent to the server.

[1416] Step 2: Receiving and analyzing battery data

[1417] The server receives battery data sent from the vehicle. The received data is analyzed and an energy usage optimization algorithm is executed. The input is the battery data sent from the terminal, and the output is the analysis result and the energy management optimization result.

[1418] Step 3: Optimize energy use

[1419] The server simulates multiple scenarios, evaluates the results, and selects the optimal energy management method. Based on the optimization results, it generates and sends specific instructions. The input is the analyzed battery data, and the output is the optimal energy management method and the corresponding instructions.

[1420] Step 4: Collect and analyze emotion data

[1421] The terminal (in the vehicle) uses cameras and microphones inside the vehicle to collect the user's facial expressions and voice. This data is analyzed by emotion analysis software to determine the user's emotional state. The input is the facial expression and voice data collected by the camera and microphone, and the output is the determined emotional state data.

[1422] Step 5: Command generation based on emotional state

[1423] The server receives the emotion analysis results and generates specific commands for the entertainment system and air conditioning system based on the emotional state. These commands are also sent to the energy management system. The input is the emotion analysis results, and the output is adjustment commands for the entertainment system and air conditioning system.

[1424] Step 6: Execute the directive

[1425] The terminal (on the vehicle side) receives commands from the server and adjusts battery charging / discharging, cooling system operation, entertainment system, and air conditioning system in real time. The input is the command from the server, and the output is the execution result of battery management and environmental adjustment.

[1426] Step 7: Monitor your battery status and adjust settings

[1427] Users can monitor the vehicle's battery status in real time through a dedicated application, and can also use the application to adjust energy management settings. The input is the operating data through the application, and the output is the adjusted energy management settings.

[1428] Step 8: Generate a prompt statement

[1429] The server generates a prompt sentence to be input to the generative AI model. This prompt sentence is generated in an appropriate form based on the overall command of the system. The input is the system state and command data, and the output is the generated prompt sentence.

[1430] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1431] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1432] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1433] [Fourth embodiment]

[1434] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1435] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1436] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1437] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1438] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1439] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1440] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1441] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1442] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1443] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1444] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1445] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1446] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1447] The present invention relates to battery systems in vehicles, and in particular to a system for improving energy efficiency and sustainability, which includes technology for monitoring the battery's condition in real time and achieving optimal energy usage.

[1448] Server Processing

[1449] The server is the heart of the present invention and performs the following processes.

[1450] 1. Receives battery measurement data (temperature, voltage, current, remaining charge) sent from the vehicle.

[1451] 2. The received measurement data is analyzed and an energy usage optimization algorithm is run, which simulates multiple scenarios, evaluates the results, and selects the optimal energy management method.

[1452] 3. Based on this selection, specific instructions are generated and sent to the vehicle's energy management system, such as load balancing, charging / discharging timing, and cooling system adjustments.

[1453] Terminal (vehicle side) processing

[1454] The terminal is installed in the vehicle and performs the following processing.

[1455] 1. Measure the battery status (temperature, voltage, current, remaining capacity) through sensors and send the data to the server at regular intervals.

[1456] 2. Receive and analyze commands sent from the server, such as "reduce energy consumption for the next hour" or "start fast charging."

[1457] 3. Based on the received commands, the system performs tasks such as charging and discharging the battery, operating the cooling system, and optimizing energy consumption in real time.

[1458] User Action

[1459] The user performs the following operations through a dedicated application.

[1460] 1. Launch the application and monitor your vehicle's battery status in real time.

[1461] 2. You can check your energy usage history through the application, such as daily energy consumption and charging / discharging schedules.

[1462] 3. Energy management settings can be adjusted through the application, such as "enable eco mode" or "delay the next charging session," allowing users to customize energy management to suit their lifestyle.

[1463] Specific examples

[1464] For example, consider the case where a vehicle's battery temperature rises on a hot day.

[1465] Terminal (vehicle side) processing: The vehicle's sensor detects a rise in battery temperature and sends that data (e.g., 45°C) to the server.

[1466] Server processing: The server receives this data and uses an algorithm to calculate the optimal course of action, resulting in a command to "activate the cooling system to lower the battery temperature."

[1467] Terminal processing: Based on the received command, the vehicle's energy management system activates the cooling system to maintain the battery temperature within an appropriate range.

[1468] User Action: The user can view this information in real time in the application. For example, the user can see that the battery temperature has dropped from 45°C to 25°C.

[1469] Through this process, the system of the present invention significantly improves battery efficiency and sustainability, extending vehicle range and battery life.

[1470] The processing flow will be explained below.

[1471] Server Processing

[1472] Step 1:

[1473] The server waits for battery measurement data to be sent from the vehicle.

[1474] Step 2:

[1475] The server receives battery measurement data sent from the vehicle, including temperature, voltage, current, and remaining energy.

[1476] Step 3:

[1477] The server analyzes the received measurement data, which includes outlier detection and data normalization.

[1478] Step 4:

[1479] The server runs an energy usage optimization algorithm based on the analyzed data, simulating multiple scenarios and evaluating the results.

[1480] Step 5:

[1481] The server selects the optimal energy management strategy and generates specific instructions based on it, including load balancing, charging and discharging timing, and cooling system adjustments.

[1482] Step 6:

[1483] The server transmits the generated command to the vehicle (terminal).

[1484] Terminal (vehicle side) processing

[1485] Step 1:

[1486] The device activates sensors to measure the battery's temperature, voltage, current, and remaining energy.

[1487] Step 2:

[1488] The terminal collects the measurement data from the sensors and assembles them into a single data packet.

[1489] Step 3:

[1490] The terminal transmits the measurement data to the server at regular intervals.

[1491] Step 4:

[1492] The terminal waits for a command sent from the server.

[1493] Step 5:

[1494] The terminal analyzes the command received from the server, including checking the type of command and how to execute it.

[1495] Step 6:

[1496] Based on the received instructions, the device charges and discharges the battery, activates the cooling system, and optimizes energy consumption.

[1497] User Action

[1498] Step 1:

[1499] The user starts a dedicated application.

[1500] Step 2:

[1501] The user requests data from the server to check the current battery status from the application.

[1502] Step 3:

[1503] The user monitors the battery status displayed in the application in real time.

[1504] Step 4:

[1505] Through the application, users can check their energy usage history, including energy consumption and charging / discharging schedules.

[1506] Step 5:

[1507] The user changes the energy management settings through the application.

[1508] Step 6:

[1509] Any changes to the user's settings are sent to the server, which then readjusts the energy management algorithms based on the settings.

[1510] This allows users to monitor battery status in real time and adjust energy management settings to suit their lifestyle.

[1511] Example 1

[1512] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1513] The aim of this invention is to improve the energy efficiency and sustainability of in-vehicle battery systems. However, conventional systems do not adequately monitor battery status in real time and perform data analysis and optimization algorithms to optimize energy usage. As a result, efficient battery use and extended battery life have been challenges.

[1514] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1515] In this invention, the server includes means for receiving measurement data and storing it in a database, means for analyzing the stored measurement data, and means for executing an energy usage optimization algorithm based on the analysis results, thereby enabling real-time monitoring of the battery status, selecting an optimal energy management method, and generating and transmitting commands, thereby enabling efficient use of the battery and extending its lifespan.

[1516] A "vehicle" is a machine that has a battery inside and moves by consuming energy.

[1517] A "battery" is a device that converts chemical energy into electrical energy and provides power for a period of time.

[1518] "Measurement data" is numerical data that indicates information about the state of the battery, and specifically includes temperature, voltage, current, and remaining energy.

[1519] A "server" is a computer system that receives, stores, analyzes, and processes data as needed.

[1520] A "database" is an information system for efficiently storing and managing large amounts of data.

[1521] "Analysis" is the act of evaluating and understanding the state and characteristics of an object based on collected data.

[1522] An "optimization algorithm" is a computational procedure for maximizing or minimizing the performance of a goal while taking into account multiple criteria.

[1523] A "command" is a specific operation instruction sent from the server to the terminal.

[1524] An "energy management system" is a system for managing and optimizing the energy consumption of batteries and vehicles.

[1525] "Real-time" refers to the immediate reflection of current status and behavior.

[1526] The present invention relates to a battery system in a vehicle, and in particular to a system for improving energy efficiency and sustainability, including technology for monitoring the state of the vehicle battery in real time to achieve optimal energy usage.

[1527] Server Processing

[1528] The server is the heart of the invention, receiving battery measurement data (temperature, voltage, current, remaining charge) sent from the vehicle and storing it in a database. The server uses MySQL or PostgreSQL as its database management system (DBMS). The stored data is analyzed and an energy usage optimization algorithm is executed. This algorithm simulates multiple scenarios and evaluates the results to select the optimal energy management method. Analysis tools such as Python's Pandas and NumPy are used for the analysis. Based on the results, specific commands (e.g., load balancing, charging / discharging timing, and cooling system adjustment) are generated and sent to the vehicle's energy management system.

[1529] Terminal (vehicle side) processing

[1530] The terminal is installed inside the vehicle and measures the battery condition through sensors, periodically sending the data to the server. A communications library is used to send the data. The terminal also receives and analyzes commands sent from the server. This analysis includes parsing the data and judging various conditions. Based on the received commands, the terminal performs real-time operations such as charging and discharging the battery, operating the cooling system, and optimizing energy consumption.

[1531] User Action

[1532] Users can monitor their vehicle's battery status in real time through a dedicated application. This application runs on a mobile device and provides the vehicle's battery status. Users can also check their past energy usage history through the application. Specifically, this includes functions to display daily energy consumption and charging / discharging schedules. In addition, they can adjust energy management settings. For example, they can enable Eco Mode or delay the next charging session.

[1533] Specific examples

[1534] For example, consider the case where a vehicle's battery temperature rises on a hot day. The device's sensor detects the rise in battery temperature and sends that data (for example, 45°C) to the server. The server receives this data, uses an algorithm to calculate the optimal response, and generates a command to "activate the cooling system to lower the battery temperature." Based on the received command, the vehicle's energy management system activates the cooling system to maintain the battery temperature within an appropriate range. The user can check this information in real time in the application. For example, they can see that the battery temperature has dropped from 45°C to 25°C.

[1535] Prompt Sentence Examples

[1536] Example prompts to input to a generative AI model:

[1537] Please write a description of the functionality of a vehicle's battery management system, including how sensors measure battery status and send that data to a server for analysis and optimization. Also, please include functionality that allows users to monitor battery status and adjust energy management through an application.

[1538] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1539] Step 1:

[1540] Server data reception

[1541] Input: Battery measurement data sent from the vehicle (temperature, voltage, current, remaining energy)

[1542] Processing: The server receives this data via HTTP communication. Specifically, the communication module parses and validates the received data.

[1543] Output: Measurement data in a format suitable for analysis

[1544] Step 2:

[1545] Server database storage

[1546] Input: Measurement data in a format suitable for analysis

[1547] Processing: The server stores the received data in a database and executes SQL queries using MySQL or PostgreSQL as the database management system (DBMS).

[1548] Output: Measurement data stored in a database

[1549] Step 3:

[1550] Server data analysis

[1551] Input: Measurement data stored in the database

[1552] Processing: The server uses Python's Pandas and NumPy to analyze the stored data, including calculating the mean, standard deviation, and outlier detection.

[1553] Output: Parsed battery data

[1554] Step 4:

[1555] Optimization algorithm execution on the server

[1556] Input: Parsed battery data

[1557] Processing: The server runs an energy usage optimization algorithm based on the analysis results. This algorithm uses Gurobi and SciPy to simulate multiple scenarios and select the optimal energy management method.

[1558] Output: Optimized energy management methods and specific directives

[1559] Step 5:

[1560] Server command generation and transmission

[1561] Input: Optimized energy management methods and specific directives

[1562] Processing: The server formats the command in JSON format and sends it to the vehicle's terminal via HTTP communication.

[1563] Output: Commands sent to the vehicle's terminal

[1564] Step 6:

[1565] Device sensor data measurement

[1566] Input: None

[1567] Processing: The terminal measures the battery status (temperature, voltage, current, remaining energy) using sensors in the vehicle, including temperature, voltage, and current sensors.

[1568] Output: Measured battery data

[1569] Step 7:

[1570] Data transmission from the device

[1571] Input: Measured battery data

[1572] Processing: The device sends the data to the server by performing an HTTP POST request using a communication library.

[1573] Output: Battery data sent to the server

[1574] Step 8:

[1575] Terminal command reception and analysis

[1576] Input: Command sent from the server

[1577] Processing: The device receives the command, analyzes the command content, parses the JSON format data, and makes a decision based on various conditions.

[1578] Output: Parsed command content

[1579] Step 9:

[1580] Terminal command execution

[1581] Input: Parsed command content

[1582] Processing: Based on the received instructions, the device will charge and discharge the battery, activate the cooling system, and optimize energy consumption in real time, such as activating the cooling system and adjusting the charging schedule.

[1583] Output: Energy management operations performed

[1584] Step 10:

[1585] Real-time user monitoring

[1586] Input: Battery data

[1587] Processing: The user launches a dedicated application, which retrieves the latest battery data from the server and displays it.

[1588] Output: Real-time updated battery status

[1589] Step 11:

[1590] Check user's past data

[1591] Input: Battery usage history for a user-specified period

[1592] Processing: The application retrieves historical data from the server and displays it to the user in the form of graphs and lists.

[1593] Output: Display of past energy usage history

[1594] Step 12:

[1595] Adjusting User Settings

[1596] Input: Energy management settings changed by the user

[1597] Processing: The user adjusts the energy management settings through the application's settings screen and sends the settings to the server.

[1598] Output: Updated Energy Management Settings

[1599] (Application example 1)

[1600] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1601] Conventional vehicle battery systems lack the technology to monitor battery status in real time and perform optimal energy management. They also lack sufficient means to provide users with timely energy management information, such as notifications of abnormal values ​​or displaying past usage history. Another issue is that it is difficult for users to adjust energy management settings via smart devices.

[1602] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1603] In this invention, the server includes a means for receiving battery measurement data and optimizing energy use, a means for sending commands to the vehicle's energy management system based on the energy use optimization, a means for displaying battery measurement data on the smart device in real time, a means for notifying of abnormal values, a means for presenting the battery energy management status as alerts or commands via the smart device, and a means for retrieving and displaying past battery usage history from a database. This enables optimal energy management by monitoring the battery status in real time and immediately notifying the user if an abnormality occurs. Furthermore, the user can easily check past usage history and adjust energy management settings via the smart device.

[1604] "Battery temperature" refers to the degree of thermal energy currently held by the battery in the vehicle.

[1605] "Voltage" refers to the potential difference produced by a vehicle's battery.

[1606] "Current" is a quantity that indicates the flow of electrons from a battery in a vehicle.

[1607] "Remaining energy" is the total amount of energy currently remaining in the vehicle's battery.

[1608] "Measurement data" refers to information about the battery's temperature, voltage, current, and remaining energy.

[1609] The "transmission means" is a communication means for sending the measurement data to the server.

[1610] The "optimization means" is a means for executing an algorithm to improve the efficiency of energy use based on the measurement data.

[1611] A "command" is an operational instruction sent to the energy management system.

[1612] A "smart device" is a multi-function device that has the ability to connect to the Internet and run applications.

[1613] The "real-time display means" is a means for displaying battery measurement data on a smart device in real time.

[1614] The "abnormal value notification means" is a means for notifying when an abnormality in the battery state is detected.

[1615] The "energy management status presentation means" is a means for presenting the optimization status of energy usage to the user as alerts or instructions via a smart device.

[1616] "Past usage history" refers to data on the battery's past voltage, current, temperature, and remaining energy.

[1617] A "database" is an information storage means for recording and saving past usage history.

[1618] This invention relates to a battery system for autonomous vehicles, and in particular to a system for improving energy efficiency and sustainability. The system measures the temperature, voltage, current, and remaining energy of the vehicle battery in real time, enabling optimal energy management.

[1619] Server Processing

[1620] The server is the core of the present invention and performs the following processes: First, it receives battery measurement data (temperature, voltage, current, remaining charge) sent from the vehicle. It analyzes this data and runs an energy usage optimization algorithm. The hardware and software used include cloud servers (e.g., AWS Lambda, Google Cloud Functions). The algorithm simulates multiple scenarios, evaluates the results, and selects the optimal energy management method. Finally, it generates and sends commands to the vehicle's energy management system based on the optimization results.

[1621] Terminal (vehicle side) processing

[1622] The terminal is installed inside the vehicle and measures the battery's status (temperature, voltage, current, remaining charge) through sensors, sending the data to a server at regular intervals. This data is displayed in real time mainly through smart devices. It also receives commands sent from the server and, based on those commands, performs tasks such as charging and discharging the battery, operating the cooling system, and optimizing energy consumption. The hardware used consists of a sensor system and communication module inside the vehicle.

[1623] User Action

[1624] Users use a dedicated smart device (e.g., smart glasses or a smartphone) to perform the following processes. First, the smart device has a function to display battery measurement data in real time. If an abnormal value is detected, an alert will be sent. In addition, past battery usage history can be retrieved from a database and easily checked through the smart device. Furthermore, users can adjust energy management settings through the smart device, which allows energy management to be optimized to suit their individual usage conditions.

[1625] Specific examples

[1626] If the battery temperature rises on a hot day, the following process occurs: The device's sensor detects a rise in battery temperature (e.g., 50°C) and sends the data to the server. The server receives this data and generates a command to activate the cooling system. This command activates the vehicle's cooling system, maintaining the battery temperature within an appropriate range (e.g., 25°C to 45°C). The user can check the change in battery temperature in real time through the smart glasses. Furthermore, if an abnormal value is detected, a prompt message will be displayed: "The current battery temperature is 50°C. Please activate the cooling system."

[1627] This allows the system of the present invention to significantly improve battery efficiency and sustainability, extending vehicle range and battery life.

[1628] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1629] Specific explanation of processing steps

[1630] Step 1: Data measurement using the terminal (vehicle side)

[1631] Sensors installed inside the vehicle measure the battery's temperature, voltage, current and remaining energy.

[1632] Input: Battery physical status (temperature, voltage, current, remaining energy)

[1633] Data processing: Each sensor converts analog data into digital form

[1634] Output: Battery status information as digital data

[1635] Step 2: Send data by device

[1636] The measured digital data of the battery is sent to the server at regular intervals.

[1637] Input: Digital data (temperature, voltage, current, remaining energy)

[1638] Data processing: Packetizing and encoding data

[1639] Output: Sent to the server as a communication packet

[1640] Step 3: Data reception and analysis by the server

[1641] The server analyzes the received battery data and runs an energy usage optimization algorithm.

[1642] Input: Battery data sent from the vehicle

[1643] Data computation: running energy optimization algorithms, simulating multiple scenarios

[1644] Output: Selection of optimal energy management method

[1645] Step 4: Optimization instructions generated by the server

[1646] Based on the optimal energy management method, a command is generated to be sent to the vehicle's energy management system.

[1647] Input: Result of optimal energy management method selection

[1648] Data processing: Command data generation and encoding

[1649] Output: Sends operation commands to the vehicle

[1650] Step 5: Receive and execute commands on the terminal (vehicle side)

[1651] The terminal on the vehicle receives commands sent from the server and operates the battery charging / discharging and cooling system based on those commands.

[1652] Input: Command data from the server

[1653] Data processing: Decoding and interpretation of command data

[1654] Output: Performing battery management actions (e.g., activating the cooling system)

[1655] Step 6: User monitors battery status

[1656] Users can use their smart devices to monitor battery status in real time.

[1657] Input: Battery data from the vehicle, command data from the server

[1658] Data calculation: Data display, abnormal value notification

[1659] Output: Visual information on smart devices

[1660] Step 7: User checks past historical data

[1661] Users can check past battery usage history via their smart device.

[1662] Input: Previously recorded battery data (retrieved from database)

[1663] Data calculation: Data search and display

[1664] Output: Display of analysis results

[1665] Step 8: User adjusts energy management settings

[1666] Users adjust energy management settings through their smart devices.

[1667] Input: Configuration data entered by the user

[1668] Data calculation: Processing of setting data, sending to server

[1669] Output: Applying adjusted energy management settings

[1670] Specific working example:

[1671] Example 1:

[1672] Step 1: A sensor inside the vehicle measures the battery temperature of 50°C and converts it into digital data.

[1673] Step 2: Send the converted digital data to the server.

[1674] Step 3: The server analyzes the received data and determines whether the cooling system needs to be activated.

[1675] Step 4: The server generates a "start cooling system" command and sends it to the vehicle.

[1676] Step 5: The vehicle's terminal receives the command and activates the cooling system.

[1677] Step 6: The user confirms through their smart device that the temperature has dropped from 50°C to 25°C.

[1678] Step 7: The user checks the battery temperature history on their smart device.

[1679] Step 8: The user adjusts the energy management settings to "Eco Mode."

[1680] Example 2:

[1681] The prompt text "The current battery temperature is 50°C. Please activate the cooling system." will be displayed on the smart device.

[1682] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1683] The present invention relates to an energy management system that combines a vehicle's battery system with a user's emotion engine, and in particular improves energy efficiency, enhances sustainability, and realizes energy management and in-vehicle environment optimization based on the user's emotional state.

[1684] Server Processing

[1685] The server is the heart of the present invention and performs the following processes.

[1686] 1. Receives battery measurement data (temperature, voltage, current, remaining charge) sent from the vehicle.

[1687] 2. The received measurement data is analyzed and an energy usage optimization algorithm is run, which simulates multiple scenarios, evaluates the results, and selects the optimal energy management method.

[1688] 3. Based on this, it generates and sends specific instructions to the vehicle's energy management system, such as load balancing, charging and discharging timing, and adjusting the cooling system.

[1689] 4. The user emotion engine is linked to the database to generate a user profile based on the emotional state.

[1690] Terminal (vehicle side) processing

[1691] The terminal is installed in the vehicle and performs the following processing.

[1692] 1. Measure the battery status (temperature, voltage, current, remaining capacity) through sensors and send the data to the server at regular intervals.

[1693] 2. Receive and analyze commands sent from the server, such as "reduce energy consumption for the next hour" or "start fast charging."

[1694] 3. Based on the received commands, the system performs tasks such as charging and discharging the battery, operating the cooling system, and optimizing energy consumption in real time.

[1695] 4. Using an emotion engine, the user's voice, facial expressions, and physiological data are analyzed to determine their emotional state.

[1696] 5. Adjust the entertainment and climate control systems in your vehicle based on your emotional state.

[1697] User Action

[1698] The user performs the following operations through a dedicated application.

[1699] 1. Launch the application and monitor your vehicle's battery status in real time.

[1700] 2. You can check your energy usage history through the application, such as daily energy consumption and charging / discharging schedules.

[1701] 3. Energy management settings can be adjusted through the application, such as "enable eco mode" or "delay the next charging session," allowing users to customize energy management to suit their lifestyle.

[1702] 4. The application works in conjunction with the emotion engine to display the user's emotional state in real time and suggest optimal energy management and environmental settings based on the user's emotional state.

[1703] Specific examples

[1704] For example, consider a case where a user looks tired in a car on a hot day.

[1705] Processing on the terminal (vehicle side): The vehicle's sensor detects a rise in battery temperature and sends that data (e.g., 45°C) to the server. The emotion engine also analyzes the user's facial expressions to determine their level of fatigue.

[1706] Server processing: The server receives battery data and user emotion data and uses an algorithm to calculate the optimal response, generating commands such as "activate the cooling system to lower the battery temperature," "play relaxing music on the entertainment system," and "adjust the heating and cooling system to maintain a comfortable room temperature."

[1707] Terminal processing: The vehicle's energy management system operates the cooling system based on commands from the server to maintain the battery temperature within an appropriate range, as well as regulating the entertainment system and air conditioning system.

[1708] User Action: The user can see these adjustments in real time in the application, ensuring optimal preferences are set based on their emotions.

[1709] Through this process, the system of the present invention not only significantly improves battery efficiency and sustainability, but also provides a comfortable in-car environment that responds to the user's emotional state.

[1710] The processing flow will be explained below.

[1711] Server Processing

[1712] Step 1:

[1713] The server waits for battery measurement data to be sent from the vehicle.

[1714] Step 2:

[1715] The server receives battery measurement data sent from the vehicle, including temperature, voltage, current, and remaining energy.

[1716] Step 3:

[1717] The server analyzes the received measurement data, including detecting outliers and normalizing the data.

[1718] Step 4:

[1719] The server runs an energy usage optimization algorithm based on the analyzed data, simulating multiple scenarios and evaluating the results.

[1720] Step 5:

[1721] The server selects the optimal energy management strategy and generates specific instructions based on it, including load balancing, charging and discharging timing, and cooling system adjustments.

[1722] Step 6:

[1723] The server transmits the generated command to the vehicle (terminal).

[1724] Step 7:

[1725] The server interfaces the user's emotion engine with the database to update the user profile based on the emotional state.

[1726] Terminal (vehicle side) processing

[1727] Step 1:

[1728] The device activates sensors to measure the battery's temperature, voltage, current, and remaining energy.

[1729] Step 2:

[1730] The terminal collects the measurement data from the sensors and assembles them into a single data packet.

[1731] Step 3:

[1732] The terminal transmits the measurement data to the server at regular intervals.

[1733] Step 4:

[1734] The terminal waits for a command sent from the server.

[1735] Step 5:

[1736] The terminal analyzes the command received from the server, including checking the type of command and how to execute it.

[1737] Step 6:

[1738] Based on the received instructions, the device charges and discharges the battery, activates the cooling system, and optimizes energy consumption.

[1739] Step 7:

[1740] The device uses an emotion engine to analyze the user's voice, facial expressions, and physiological data to determine their emotional state.

[1741] Step 8:

[1742] The terminal sends commands to the system to adjust the entertainment system and air conditioning system in the vehicle depending on the emotional state.

[1743] User Action

[1744] Step 1:

[1745] The user starts a dedicated application.

[1746] Step 2:

[1747] The user requests data from the server to check the current battery status from the application.

[1748] Step 3:

[1749] The user monitors the battery status displayed in the application in real time.

[1750] Step 4:

[1751] Through the application, users can check their energy usage history, including energy consumption and charging / discharging schedules.

[1752] Step 5:

[1753] The user changes the energy management settings through the application.

[1754] Step 6:

[1755] Any changes to the user's settings are sent to the server, which then readjusts the energy management algorithms based on the settings.

[1756] Step 7:

[1757] Users can see the results of the emotion engine in real time through the application.

[1758] Step 8:

[1759] The user can check the application for suggestions for optimal energy management and environmental settings based on their emotional state and make adjustments as needed.

[1760] This allows users to monitor battery status in real time and adjust energy management settings to suit their lifestyle, while the emotion engine provides adaptive environmental adjustments to provide a more comfortable driving experience.

[1761] Example 2

[1762] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1763] In modern vehicles, it is difficult to simultaneously optimize energy management and user comfort. In particular, efficient management of energy storage devices and adjustment of the in-vehicle environment based on the user's emotional state are required, but a system that controls these in an integrated manner is lacking. This leads to issues such as reduced energy efficiency and reduced user comfort.

[1764] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1765] In this invention, the server includes means for measuring the temperature, voltage, current, and remaining energy of an energy storage device in the vehicle, means for periodically transmitting measurement data from the energy storage device, means for receiving the measurement data from the energy storage device and optimizing energy use, means for simulating multiple energy consumption scenarios and evaluating the results to select an optimal energy management method, and means for detecting the emotional state of the user and adjusting environmental settings in the vehicle based on the emotional state, thereby enabling both improved energy efficiency and user comfort.

[1766] An "energy storage device" is a device for storing electricity within a vehicle, and mainly refers to batteries and capacitors.

[1767] "Measurement data" refers to data that represents physical quantities such as the temperature, voltage, current, and remaining energy of the energy storage device.

[1768] "Energy use optimization" refers to calculating and adjusting efficient energy management and usage methods based on received measurement data.

[1769] A "command" is a specific instruction sent from the server to the terminal to prompt changes to the settings of the energy storage device or the in-vehicle environment.

[1770] "Energy management system" means a system for efficiently managing the supply and use of energy in a vehicle.

[1771] "Emotional state" refers to a psychological state inferred from a user's voice, facial expression, and physiological data.

[1772] "Environmental settings" refers to settings that adjust the in-car entertainment system, air conditioning system, etc.

[1773] An "entertainment system" is a system that provides entertainment such as music playback, video playback, and games in a vehicle.

[1774] An "air conditioning system" is a system that adjusts the temperature and humidity inside a vehicle to provide a comfortable environment.

[1775] "Real-time" means that the system processes data immediately and provides information or takes action nearly instantaneously in real time.

[1776] To implement this invention, the following hardware and software are required: a sensor for measuring the status of an energy storage device installed in a vehicle, a communication module for periodically transmitting data, a server for receiving and analyzing the data, an emotion engine for analyzing the user's emotional state and adjusting the in-car environment, and a smartphone application for the user to monitor and adjust the system in real time.

[1777] The server is the heart of the present invention and performs the following functions: Receives measurement data (temperature, voltage, current, remaining charge) from the energy storage device sent from the vehicle. The received data is analyzed using machine learning algorithms using Python and TensorFlow. This optimizes energy use by simulating multiple energy consumption scenarios and selecting the optimal method. Based on the optimal energy management method selected, the server then generates and sends specific commands to the vehicle's energy management system. Examples include load balancing, charging and discharging timing, and activating the cooling system. The server also uses a user emotion engine to analyze the user's voice, facial expressions, and physiological data to generate a user profile based on their emotional state.

[1778] The terminal (vehicle side) is responsible for measuring the status of the energy storage device and periodically transmitting this data to a server. Specifically, it is equipped with sensors that measure the temperature, voltage, current, and remaining energy inside the vehicle. The data is transmitted to the server at regular intervals, and the terminal receives and analyzes commands sent from the server. These commands include reducing energy consumption and starting fast charging. Based on the received commands, the terminal then performs real-time operations such as charging and discharging, activating the cooling system, and optimizing energy consumption. The terminal also uses an emotion engine to analyze the user's voice, facial expression, and physiological data to determine their emotional state. Depending on the emotional state, the terminal adjusts the entertainment system and air conditioning system to improve user comfort.

[1779] Users operate a dedicated application on their smartphone. This application, developed using Flutter and React Native, allows them to monitor the status of the vehicle's energy management system in real time. Through the application, users can check their past energy usage history and adjust energy management settings. For example, they can set things like "enable eco mode" or "delay the next charging session." In addition, the application works with an emotion engine to display the user's emotional state in real time and suggests optimal energy management and environmental settings based on their emotional state.

[1780] As a concrete example, consider a case where a user looks tired while in the car on a hot day. At this time, a sensor on the device (in the vehicle) detects a rise in battery temperature and sends that data (e.g., 45°C) to the server. The emotion engine also analyzes the user's facial expression and determines the level of fatigue. The server receives this data and, based on the analysis results, generates commands such as "activate the cooling system," "play relaxing music," and "set the room temperature to a comfortable level." These commands are sent to the device, which then operates the cooling system, adjusts the entertainment system, and sets the air conditioning system in accordance with the commands. The user can then check these adjustments on their smartphone application and confirm that the optimal environmental settings based on their emotional state have been implemented.

[1781] Examples of input prompts for a generative AI model include:

[1782] Please explain the detailed operational flow of the energy management system in a situation where the user looks tired in the car on a hot day. Please explain each step specifically from the perspective of the server, the terminal (in the car), and the user.

[1783] As described above, the present invention can be implemented by integrating various hardware and software in order to achieve both efficient management of the energy storage device and user comfort.

[1784] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1785] Step 1:

[1786] Battery status measurement and data transmission on the terminal (vehicle side)

[1787] The terminal (vehicle side) uses sensors installed inside the vehicle to measure the temperature, voltage, current, and remaining energy of the energy storage device. The measurement data is collected, for example, every 10 minutes. This data is collected in the telematics unit via the vehicle's CAN bus and periodically sent to the server.

[1788] Input: Battery measurement data from in-vehicle sensors (temperature, voltage, current, remaining capacity)

[1789] Data processing or data calculation: Aggregation of measurement data, shaping of time series data

[1790] Output: Transmission of measurement data from the telematics unit to the server

[1791] Step 2:

[1792] Server data reception and analysis

[1793] The server receives measurement data sent from the terminal (vehicle side). After receiving this data, it is stored in a database and an energy usage optimization algorithm is executed. A machine learning algorithm using Python and TensorFlow analyzes the measurement data and calculates the optimal energy management method.

[1794] Input: Measurement data sent from the device (temperature, voltage, current, remaining capacity)

[1795] Data processing or data calculation: receiving data, storing it in a database, and analyzing it with machine learning algorithms

[1796] Output: Calculation results of optimal energy management method

[1797] Step 3:

[1798] Server command generation

[1799] The server generates specific commands based on the analysis results. These commands include, for example, "reduce energy consumption for the next hour," "start rapid charging," and "activate the cooling system." These commands are then sent back to the terminal (vehicle side).

[1800] Input: Calculation result of optimal energy management method

[1801] Data processing or data calculation: Creation of specific commands using command generation logic

[1802] Output: Specific instructions sent to the terminal

[1803] Step 4:

[1804] Terminal (vehicle side) command reception and execution

[1805] The device receives and analyzes instructions sent from the server, and based on the instructions, performs operations in real time, such as charging and discharging the battery, activating the cooling system, and optimizing energy consumption.

[1806] Input: Specific instructions sent by the server

[1807] Data processing or data calculation: parsing commands and executing control logic for battery management systems and cooling systems

[1808] Output: Specific operation (start of charging / discharging, start of cooling system, etc.)

[1809] Step 5:

[1810] Emotion analysis on the device (vehicle side)

[1811] The device uses cameras and microphones inside the vehicle to collect the user's voice, facial expressions, and physiological data, and analyzes them using an emotion engine. Based on the analysis results, the device determines the user's emotional state.

[1812] Input: User voice, facial expressions, physiological data

[1813] Data processing or data calculation: Emotion analysis using image processing software (OpenCV) and voice analysis tool (Praat)

[1814] Output: Determined user's emotional state

[1815] Step 6:

[1816] Terminal (vehicle side) environment adjustment

[1817] Based on the emotion analysis results, the device can adjust the vehicle's entertainment and climate control systems, for example, playing relaxing music and setting the temperature to a comfortable level if the user is tired.

[1818] Input: Emotion analysis results, environmental adjustment instructions from the server

[1819] Data processing or data calculation: Executing control logic for entertainment systems or air conditioning systems

[1820] Output: Controlled in-car environment (playing music, changing climate settings, etc.)

[1821] Step 7:

[1822] Real-time user monitoring and configuration adjustment

[1823] Users can monitor the status of their vehicle's energy management system in real time and check past energy usage history through a smartphone application. They can also adjust energy management settings through the application, such as enabling Eco Mode or delaying the next charging session.

[1824] Input: Status data from the vehicle's energy management system, user configuration change requests

[1825] Data processing or data calculation: Visualization of status data, execution of energy management setting logic

[1826] Output: Real-time monitoring screen, setting change results

[1827] This completes a series of processes, enabling efficient management of the vehicle's energy storage device and providing a comfortable in-vehicle environment that suits the user's emotional state.

[1828] (Application example 2)

[1829] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1830] Vehicle energy management systems are required to improve battery energy efficiency and realize an optimal in-car environment that responds to the user's emotional state. It is also important that real-time battery status monitoring and energy management settings are easy for users to understand and operate intuitively. To solve these issues, energy management based on the user's emotional state is necessary in addition to optimizing energy use.

[1831] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving battery data transmitted from the vehicle and optimizing energy use, means for analyzing the user's emotional state and generating commands based on the emotional state, and means for generating prompt sentences to be input to the generative AI model. This makes it possible to use energy efficiently and provide a comfortable in-vehicle environment based on the user's emotions.

[1832] "Battery measurement data" refers to various indicators such as the temperature, voltage, current, and remaining energy of the battery inside the vehicle.

[1833] "Energy use optimization" refers to the process of planning and implementing efficient energy usage methods based on battery data.

[1834] An "energy management system" is a system that optimally controls and manages various energy systems, including batteries, inside a vehicle.

[1835] The "user's emotional state" refers to the emotions expressed by the user, and is analyzed from voice, facial expressions, physiological data, and the like.

[1836] "Emotion analysis software" is software that analyzes a user's facial expressions and voice data to determine their emotional state.

[1837] "Real-time execution" means that the entire process, from data acquisition to processing to command execution, occurs with almost no delay.

[1838] A "generative AI model" is a model of artificial intelligence that is trained to perform a specific task.

[1839] A "prompt" is an instruction or question that is input into a generative AI model.

[1840] To implement this invention, the system provides a technology for efficiently managing the battery status in a vehicle and optimizing the in-vehicle environment based on the emotional state of the user. The system configuration and processing details are described below.

[1841] System Program Overview

[1842] This system consists of three main elements: a server, a terminal (in the vehicle), and a user.

[1843] Server Processing

[1844] The server is the center of the system and performs the following processes:

[1845] 1. Receiving and analyzing battery data:

[1846] Receives battery measurement data (temperature, voltage, current, remaining energy) sent from the vehicle.

[1847] It analyzes the received battery data and runs energy usage optimization algorithms.

[1848] 2. Optimizing energy use:

[1849] Multiple scenarios are simulated, the results are evaluated, and the optimal energy management method is selected.

[1850] Based on the optimization results, specific instructions are generated and sent to the vehicle's energy management system.

[1851] 3. Emotion data analysis and command generation:

[1852] Emotion analysis software is used to analyze the user's facial expressions and voice to determine their emotional state.

[1853] Generates commands to entertainment and air conditioning systems based on emotional state.

[1854] 4. Prompt generation:

[1855] Generate prompt sentences to input to the generative AI model.

[1856] Terminal (vehicle side) processing

[1857] The terminal is installed in the vehicle and performs the following processes.

[1858] 1. Battery data measurement and transmission:

[1859] Sensors measure the battery's status (temperature, voltage, current, remaining energy) and periodically send the data to a server.

[1860] 2. Receiving and executing orders:

[1861] Receives and analyzes instructions sent from the server.

[1862] Based on the received commands, it adjusts battery charging and discharging, cooling system operation, and entertainment and air conditioning systems in real time.

[1863] User Action

[1864] The user performs the following operations through a dedicated application.

[1865] 1. Battery status monitoring:

[1866] Launch the application and monitor your vehicle's battery status in real time.

[1867] You can check your past energy usage history through the application.

[1868] 2. Adjust Energy Management Settings:

[1869] Adjust energy management settings, such as "Enable Eco Mode" or "Delay next charging session."

[1870] 3. Reflection of emotional state:

[1871] Optimal energy management and environmental settings are suggested based on the user's emotional state.

[1872] Specific examples

[1873] For example, consider a case where a user looks tired in a car on a hot day.

[1874] 1. Terminal (vehicle side) processing:

[1875] Sensors in the vehicle measure the battery temperature and send the data to a server, while emotion analysis software determines the user's level of fatigue.

[1876] 2. Server processing:

[1877] The server analyzes battery data and emotional data and generates commands such as "start the cooling system," "play relaxing music," and "adjust the air conditioning system."

[1878] 3. Terminal processing:

[1879] The vehicle's energy management system regulates the cooling system, entertainment system, and air conditioning system based on commands from the server.

[1880] Prompt Sentence Examples

[1881] "The battery temperature of the autonomous vehicle has reached 45°C. The user's facial expression indicates that they are tired. Please generate optimal commands."

[1882] In this way, the system of the present invention realizes efficient energy utilization and provides a comfortable in-vehicle environment based on the user's emotions.

[1883] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1884] Step 1: Measuring and sending battery data

[1885] The terminal (vehicle side) uses sensors installed inside the vehicle to measure various indicators such as the battery temperature, voltage, current, and remaining energy. The measured data is sent to the server at regular intervals. The input is the measurement data from the sensors, and the output is the battery data sent to the server.

[1886] Step 2: Receiving and analyzing battery data

[1887] The server receives battery data sent from the vehicle. The received data is analyzed and an energy usage optimization algorithm is executed. The input is the battery data sent from the terminal, and the output is the analysis result and the energy management optimization result.

[1888] Step 3: Optimize energy use

[1889] The server simulates multiple scenarios, evaluates the results, and selects the optimal energy management method. Based on the optimization results, it generates and sends specific instructions. The input is the analyzed battery data, and the output is the optimal energy management method and the corresponding instructions.

[1890] Step 4: Collect and analyze emotion data

[1891] The terminal (in the vehicle) uses cameras and microphones inside the vehicle to collect the user's facial expressions and voice. This data is analyzed by emotion analysis software to determine the user's emotional state. The input is the facial expression and voice data collected by the camera and microphone, and the output is the determined emotional state data.

[1892] Step 5: Command generation based on emotional state

[1893] The server receives the emotion analysis results and generates specific commands for the entertainment system and air conditioning system based on the emotional state. These commands are also sent to the energy management system. The input is the emotion analysis results, and the output is adjustment commands for the entertainment system and air conditioning system.

[1894] Step 6: Execute the directive

[1895] The terminal (on the vehicle side) receives commands from the server and adjusts battery charging / discharging, cooling system operation, entertainment system, and air conditioning system in real time. The input is the command from the server, and the output is the execution result of battery management and environmental adjustment.

[1896] Step 7: Monitor your battery status and adjust settings

[1897] Users can monitor the vehicle's battery status in real time through a dedicated application, and can also use the application to adjust energy management settings. The input is the operating data through the application, and the output is the adjusted energy management settings.

[1898] Step 8: Generate a prompt statement

[1899] The server generates a prompt sentence to be input to the generative AI model. This prompt sentence is generated in an appropriate form based on the overall command of the system. The input is the system state and command data, and the output is the generated prompt sentence.

[1900] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1901] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1902] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1903] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1904] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1905] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1906] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1907] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1908] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1909] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1910] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1911] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1912] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1913] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[1914] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1915] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1916] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1917] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1918] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1919] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1920] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1921] The following is further disclosed regarding the above embodiment.

[1922] (Claim 1)

[1923] means for measuring the temperature, voltage, current, and remaining energy of a battery in a vehicle;

[1924] means for periodically transmitting measurement data of the battery;

[1925] means for receiving measurement data of the battery and optimizing energy usage;

[1926] means for sending commands to an energy management system of the vehicle based on the energy usage optimization;

[1927] The system includes means for adjusting the condition of the battery based on said command.

[1928] (Claim 2)

[1929] 2. The system according to claim 1, wherein the energy usage optimization means simulates a plurality of scenarios, evaluates the results, and selects an optimal energy management method.

[1930] (Claim 3)

[1931] 10. The system of claim 1, further comprising a user application for monitoring the vehicle's battery status in real time, the user being able to view the battery status and adjust energy management settings through the application.

[1932] "Example 1"

[1933] (Claim 1)

[1934] means for measuring the temperature, voltage, current, and remaining energy of a battery in a vehicle;

[1935] means for periodically transmitting measurement data of the battery;

[1936] means for receiving measurement data of the battery and storing it in a database;

[1937] means for analyzing the stored measurement data;

[1938] means for executing an energy usage optimization algorithm based on the analysis results;

[1939] means for generating and transmitting commands to an energy management system of the vehicle based on the results of said algorithm;

[1940] The system includes a means for charging and discharging the battery, operating the cooling system, and optimizing energy consumption in real time based on the instructions.

[1941] (Claim 2)

[1942] 2. The system according to claim 1, wherein the system simulates multiple scenarios based on the results of the energy usage optimization algorithm, evaluates the results of the scenarios, and selects the optimal energy management method.

[1943] (Claim 3)

[1944] 10. The system of claim 1, further comprising a user interface for monitoring the vehicle's battery status in real time, the user interface enabling a user to view the battery status and adjust energy management settings.

[1945] "Application Example 1"

[1946] (Claim 1)

[1947] means for measuring the temperature, voltage, current, and remaining energy of a battery in a vehicle;

[1948] means for periodically transmitting measurement data of the battery;

[1949] means for receiving measurement data of the battery and optimizing energy usage;

[1950] means for sending commands to an energy management system of the vehicle based on the energy usage optimization;

[1951] means for adjusting the state of the battery based on said command;

[1952] a means for displaying the measurement data of the battery on a smart device in real time;

[1953] means for notifying the smart device of an abnormal value;

[1954] means for presenting battery energy management status as alerts or commands through the smart device;

[1955] The system includes a means for retrieving and displaying past battery usage history from a database.

[1956] (Claim 2)

[1957] 2. The system according to claim 1, wherein the energy usage optimization means simulates a plurality of scenarios, evaluates the results, and selects an optimal energy management method.

[1958] (Claim 3)

[1959] 10. The system of claim 1, further comprising an application for a smart device for monitoring the vehicle's battery status in real time, wherein the application allows a user to view the battery status and adjust energy management settings.

[1960] "Example 2: Combining Emotion Engines"

[1961] (Claim 1)

[1962] means for measuring the temperature, voltage, current, and remaining energy of an energy storage device in the vehicle;

[1963] means for periodically transmitting measurement data of the energy storage device;

[1964] means for receiving measurement data of the energy storage device and optimizing energy usage;

[1965] a means for simulating a plurality of energy consumption scenarios by the energy usage optimization means, evaluating the results, and selecting an optimal energy management method;

[1966] means for sending commands to an energy management system of the vehicle based on the energy usage optimization;

[1967] means for detecting an emotional state of a user and adjusting environmental settings within the vehicle based on the emotional state;

[1968] and means for adjusting a state of the energy storage device based on said command.

[1969] (Claim 2)

[1970] 10. The system according to claim 1, further comprising an emotion analysis means for determining the emotional state of the user in real time and adjusting the entertainment system and air conditioning system in the vehicle.

[1971] (Claim 3)

[1972] 10. The system of claim 1, further comprising a user application for monitoring the vehicle's energy management status in real time, through which the user can view the energy management status and adjust energy management settings.

[1973] "Application example 2 when combining emotion engines"

[1974] (Claim 1)

[1975] means for measuring the temperature, voltage, current, and remaining energy of a battery in a vehicle;

[1976] means for periodically transmitting measurement data of the battery;

[1977] means for receiving measurement data of the battery and optimizing energy usage;

[1978] means for sending commands to an energy management system of the vehicle based on the energy usage optimization;

[1979] means for adjusting the state of the battery based on said command;

[1980] means for analyzing the emotional state of a user and adjusting an entertainment system or an air conditioning system based on the emotional state;

[1981] A means for analyzing a user's facial expressions and voice using emotion analysis software and suggesting optimal energy management based on the user's emotional state;

[1982] means for adjusting entertainment and air conditioning systems in real time based on said emotional state;

[1983] A means of generating prompt sentences to input to a generative AI model

[1984] A system including:

[1985] (Claim 2)

[1986] 2. The system according to claim 1, wherein the energy usage optimization means simulates a plurality of scenarios, evaluates the results, and selects an optimal energy management method.

[1987] (Claim 3)

[1988] 10. The system of claim 1, further comprising a user application for monitoring the vehicle's battery status in real time, the user being able to view the battery status and adjust energy management settings through the application. [Explanation of symbols]

[1989] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. means for measuring the temperature, voltage, current, and remaining energy of a battery in a vehicle; means for periodically transmitting measurement data of the battery; means for receiving measurement data of the battery and optimizing energy usage; means for sending commands to an energy management system of the vehicle based on the energy usage optimization; The system includes means for adjusting the condition of the battery based on said command.

2. 2. The system according to claim 1, wherein the energy usage optimization means simulates a plurality of scenarios, evaluates the results, and selects an optimal energy management method.

3. 10. The system of claim 1, further comprising a user application for monitoring the vehicle's battery status in real time, the user being able to view the battery status and adjust energy management settings through the application.

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