Tire state identification system, vehicle, vehicle management system, program, and tire state identification method

Abstract

One aspect of the present invention provides a tire state identification system comprising at least one processor. The at least one processor acquires outside air temperature information indicating an outside air temperature of a vehicle and use state information indicating a use state of the vehicle, identifies a state of a tire of the vehicle on the basis of the outside air temperature information and the use state information, and outputs tire state information indicating the state of the tire. In one aspect of the present invention, the use state information includes information indicating the operation time of the vehicle.

Description

Tire Condition Identification System, Vehicle, Vehicle Management System, Program, and Tire Condition Identification Method

[0008]

[0001] The present invention relates to a tire condition identification system, a vehicle, a vehicle management system, a program, and a tire condition identification method.

[0002] Patent Document 1 describes estimating the temperature of air in the internal cavity of a tire of a vehicle in motion. [Prior Art Documents] [Patent Documents] [Patent Document 1] U.S. Patent No. 7,043,973

[0003] During the running of a vehicle, the temperature of the tire may rise and the tire may malfunction. Therefore, it is desired to accurately identify the temperature of the tire.

[0004] In one embodiment, a tire condition identification system including at least one processor is provided. The at least one processor acquires outside air temperature information indicating the outside air temperature of the vehicle and usage state information indicating the usage state of the vehicle, identifies the condition of the tire equipped on the vehicle based on the outside air temperature information and the usage state information, and outputs tire condition information indicating the condition of the tire.

[0005] Note that the above summary of the invention does not list all the features of the present invention. Sub - combinations of these feature groups can also be inventions.

[0006] Shows the configuration of the vehicle management system 100. Shows the configuration of the vehicle 102. Shows the configuration of the vehicle 112. Shows the configuration of the management device 108. Shows an example of a learning model for identifying the condition of a tire. Shows an example of the processing flow of the control device 250. Shows an example of the computer 1200.

[0007] The following embodiments do not limit the invention according to the claims. Not all combinations of features described in the embodiments are essential for the solution means of the invention.

[0008] Various embodiments may be described with reference to flowcharts or configuration diagrams. Each block in a flowchart or functional configuration diagram may represent (1) a stage in a process in which an operation is performed, or (2) a section of equipment that has the role of performing the operation. Certain stages and sections may be implemented by dedicated circuits, programmable circuits supplied with computer-readable instructions stored on a computer-readable medium, and / or processors supplied with computer-readable instructions stored on a computer-readable medium. Dedicated circuits may include digital and / or analog hardware circuits, and may include integrated circuits (ICs) and / or discrete circuits. Programmable circuits may include reconfigurable hardware circuits, including logic AND, logic OR, logic XOR, logic NAND, logic NOR, and other logic operations, flip-flops, registers, field-programmable gate arrays (FPGAs), programmable logic arrays (PLAs), and other memory elements.

[0009] Computer-readable media may include any tangible device capable of storing instructions to be executed by a suitable device, and as a result, computer-readable media having instructions stored therein will comprise a product that includes instructions that can be executed to create means for performing operations specified in a flowchart or diagram. Examples of computer-readable media may include electronic storage media, magnetic storage media, optical storage media, electromagnetic storage media, semiconductor storage media, etc. More specific examples of computer-readable media may include floppy disks (registered trademark), diskettes, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), electrically erasable programmable read-only memory (EEPROM), static random access memory (SRAM), compact disk read-only memory (CD-ROM), digital multipurpose disc (DVD), Blu-ray (registered trademark) disc, memory stick, integrated circuit card, etc.

[0010] Computer-readable instructions may include assembler instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, state setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Smalltalk®, Java®, C++, and conventional procedural programming languages ​​such as the C programming language or similar programming languages.

[0011] Computer-readable instructions may be provided locally or via a wide area network (WAN) such as a local area network (LAN) or the internet to the processor or programmable circuit of a programmable data processing device such as a computer. The computer may execute computer-readable instructions to create means for performing operations specified in a flowchart or configuration diagram. Here, the computer may be a PC (personal computer), tablet computer, smartphone, workstation, server computer, general-purpose computer, or special-purpose computer, and may also be a computer system in which multiple computers are connected. Such a computer system in which multiple computers are connected is also called a distributed computing system and is a computer in a broad sense. In a distributed computing system, multiple computers execute a part of the program, and as needed, data during program execution is passed between computers, so that multiple computers execute the program collectively.

[0012] Examples of processors include computer processors, central processing units (CPUs), processing units, microprocessors, digital signal processors, controllers, and microcontrollers. A computer may have one or more processors. In a multiprocessor system with multiple processors, each processor executes a portion of the program, and the processors collectively execute the program by passing program execution data between them as needed. For example, in the execution of multitasks, each of the multiple processors may execute a portion of each task in small chunks by switching tasks at each time slice. In this case, which part of a program each processor executes changes dynamically. Which part of a program each of the multiple processors executes may also be statically determined by multiprocessor-aware programming.

[0013] Figure 1 shows the configuration of a vehicle management system 100 according to one embodiment. The vehicle management system 100 comprises a vehicle 102, a communication network 106, a management device 108, a data server 110, and a vehicle 112. Vehicle 102 is equipped with a tire sensor 104. Vehicle 112 is not equipped with a tire sensor. Vehicle 102, the management device 108, the data server 110, and vehicle 112 are connected to each other via the communication network 106. Each of the vehicle management system 100, vehicle 102, data server 110, and vehicle 112, and any combination thereof, is an example of a tire condition identification system. Vehicles 102 and 112 are work vehicles equipped with front wheels and rear wheels. Vehicles 102 and 112 are used, for example, to drive and perform work at work sites such as mines. Vehicles 102 and 112 are work vehicles such as dump trucks, wheel loaders, or motor graders. Vehicles 102 and 112 may be either manned or unmanned. A manned vehicle is one that is driven by an onboard driver. An unmanned vehicle is one that operates without the need for driver operation and can function even without an onboard driver. Vehicles 102 and 112 may work in the same mine or the same construction site or other work location. Vehicles 102 and 112 may have the same configuration or functions.

[0014] The management device 108 may be located in a different location from the work site where vehicles 102 and 112 are working. In this case, the management device 108 communicates with vehicles 102 and 112 via a communication network 106 such as the Internet, a cellular network such as 4G, 5G, or 6G, or a satellite communication network. The management device 108 may be located at the work site where vehicles 102 and 112 are working. In this case, the management device 108 communicates with vehicles 102 and 112 via a communication network 106 such as a local network (LAN). The LAN may be a wireless LAN such as Wi-Fi®. The management device 108 may also communicate with vehicles 102 and 112 using short-range wireless communication such as Bluetooth®. Vehicles 102 and 112 communicate with each other via the communication network 106 or using short-range wireless communication such as Bluetooth®.

[0015] Vehicle 102 collects tire condition information indicating the condition of the tires, usage status information indicating the usage status of vehicle 102, and external factor information indicating the external condition of vehicle 102. The tire condition may be the internal condition of the tires. The tire sensor 104 is, for example, a tire pressure monitoring system (TPMS). Vehicle 102 transmits the collected information to the management device 108 or data server 110 via the communication network 106. The data server 110 stores the information received from vehicle 102 and provides it in response to requests from the management device 108, vehicle 102, or vehicle 112.

[0016] The management device 108 acquires various information from the vehicle 102 or the data server 110 via the communication network 106. Based on the various information, the management device 108 generates a learning model or algorithm for identifying the tire status. A vehicle control device incorporating the learning model or algorithm generated by the management device 108 is manufactured and installed in the vehicle 102 and the vehicle 112. The management device 108 may also transmit the learning model or algorithm to the control device installed in the vehicle 102 or the vehicle 112.

[0017] Vehicle 112 collects usage status information and external factor information. The control device mounted on vehicle 112 uses a learning model or algorithm generated by the management device 108 to identify the tire status from the usage status information and external factor information of vehicle 112, and outputs estimated tire status information indicating the identified tire status. The control device of vehicle 112 displays notifications regarding the tire status to the operator of vehicle 112. For example, if the tire temperature or pressure exceeds a predetermined temperature or pressure, a warning is displayed prompting the operator to review the driving conditions of vehicle 112. Examples of warnings prompting a review of driving conditions include warnings to reduce driving speed, warnings to reduce load, warnings to review the road being driven on, and warnings to stop.

[0018] Vehicle 112 may transmit at least one of the collected information and estimated tire condition information to the management device 108 or data server 110 via the communication network 106. The data server 110 stores the information and estimated tire condition information received from vehicle 112 and outputs it in response to requests from the management device 108, vehicle 102, or vehicle 112. Here, "output" means outputting to an external location of the data server 110, and is a concept that includes visual display or transmission via the communication network.

[0019] The management device 108 may transmit the estimated tire status information output from the data server 110 to a computer in response to a request from a computer used by the operator of the vehicle 102, the user of the management device 108, the operator of the vehicle 112, or other workers. The computer may display the estimated tire status information transmitted by the management device 108 using a web application.

[0020] The management device 108 acquires usage status information and external factor information of the vehicle 112 from the vehicle 112 or the data server 110 via the communication network 106. The management device 108 uses a generated learning model or algorithm to identify the tire status from the usage status information and external factor information of the vehicle 112. The management device 108 displays a notification regarding the tire status to the user of the management device 108. For example, a report is created and displayed indicating that the temperature or pressure of the vehicle 112's tires exceeds a predetermined temperature or pressure. The management device 108 may transmit the notification regarding the tire status to the vehicle 112 via the communication network 106. The control device of the vehicle 112 may display the notification regarding the tire status to the operator of the vehicle 112.

[0021] The tire condition of vehicle 112, which is not equipped with tire sensors, can be accurately identified. The control device of vehicle 112 can prompt the operator of vehicle 112 to take measures to avoid tire failure, such as slowing down. If vehicle 102 is an unmanned vehicle, the manager of the management device 108 or other worker can send instructions to vehicle 102, such as slowing down. The user of the management device 108 can understand the tire condition with high accuracy, so measures can be taken to prevent tire damage caused by rising tire temperature or pressure. Therefore, the vehicle management system 100 can achieve low-cost operation (LCO). In mining sites, multiple vehicles may travel between loading and unloading areas using the same road, so by attaching a tire sensor to one vehicle and generating a learning model, the tire condition of vehicles without tire sensors can be identified.

[0022] Figure 2 shows the configuration of a vehicle 102 according to this embodiment. The vehicle 102 includes a plurality of tires 202, a plurality of fluid pressure suspensions 204, an engine 206, a cooler 208, at least one tire sensor 104, a usage state detection device 220, an external factor measurement device 240, a control device 250, a communication device 270, and an output device 280. The control device 250 is an example of a tire condition identification system.

[0023] A fluid-pressure suspension 204 is connected to some or all of the multiple tires 202. A cooler 208 is connected to the engine 206. A tire sensor 104 is installed on at least one of the multiple tires 202. A tire sensor 104 may be installed on all of the multiple tires 202. The tire sensor 104 may be installed inside the tire 202. The tire sensor 104 measures the state of the tire 202 and outputs tire state information indicating the state of the tire 202 to the control device 250. The state of the tire 202 is at least one of the temperature and pressure of the tire 202. The tire sensor 104 may measure the internal state of the tire 202 and output tire state information indicating the internal state of the tire 202 to the control device 250. The internal state of the tire 202 is at least one of the temperature and pressure inside the tire 202.

[0024] The usage status detection device 220 detects the usage status of the vehicle 102 and outputs usage status information indicating the usage status of the vehicle 102 to the control device 250. The usage status information may include information indicating the operating time (SMR) of the vehicle 102, information indicating the continuous operating time which is the time the vehicle 102 is in continuous operation, information indicating the load on the tires 202 of the vehicle 102, information indicating the distance traveled by the vehicle 102, information indicating the speed of the vehicle 102, information indicating the rotational speed of the engine 206, and information indicating the temperature of the coolant in the cooler 208.

[0025] An example of information indicating the load on the tires 202 of vehicle 102 is information indicating the mass of vehicle 102 and the load loaded on vehicle 102. The travel distance of vehicle 102 is, for example, the total travel distance, which is the distance traveled by vehicle 102 from the time of manufacture of vehicle 102; the operating travel distance, which is the distance traveled by vehicle 102 from the time the engine of vehicle 102 is started until the travel distance is measured; or the continuous travel distance, which is the distance traveled by vehicle 102 continuously without stopping from the time it starts traveling until the travel distance is measured. Usage status information may be time-series data. An example of usage status information is a value obtained by accumulating the time-series data of usage status information over operating time or continuous operating time.

[0026] The operating status detection device 220 includes a pressure sensor 224, a rotation sensor 226, a cooler temperature sensor 228, a speed sensor 230, an odometer 232, and a timer 234. The pressure sensor 224 is connected to the fluid pressure suspension 204. The rotation sensor 226 is connected to the engine 206. The cooler temperature sensor 228 is connected to the cooler 208.

[0027] The pressure sensor 224 measures the pressure of the fluid-pressure suspension 204. The rotation sensor 226 measures the rotational speed of the engine 206. The cooler temperature sensor 228 measures the temperature of the coolant in the cooler 208. The speed sensor 230 measures the speed of the vehicle 102. The odometer 232 measures the distance traveled by the vehicle 102. The timer 234 measures the operating time or continuous operating time of the vehicle 102. The pressure of the fluid-pressure suspension 204 is an example of information indicating the mass of the vehicle 102 and the cargo loaded on the vehicle 102.

[0028] The external factor measuring device 240 measures the external conditions of the vehicle 102 and outputs external factor information indicating the external conditions of the vehicle 102 to the control device 250. The external factor information may include external temperature information indicating the outside temperature of the vehicle 102, information indicating the time, or information indicating the location of the vehicle 102.

[0029] The external factor measurement device 240 includes an outside temperature sensor 242, a clock 244, and a position sensor 246. The outside temperature sensor 242 measures the outside temperature of the vehicle 102. The clock 244 measures the time, such as the month, date, or hour. The position sensor 246 measures the position of the vehicle 102. The position sensor 246 may be a GNSS (Global Navigation Satellite System).

[0030] The control device 250 includes an information acquisition unit 252, an information storage unit 254, a state identification unit 256, a communication control unit 258, and an output control unit 260. The information acquisition unit 252 acquires tire status information for at least one tire 202, vehicle usage status information for the vehicle 102, and external factor information for the vehicle 102. The information storage unit 254 stores the tire status information, usage status information, and external factor information acquired by the information acquisition unit 252 in association with each other. The information acquisition unit 252 may acquire tire status information in association with information for identifying the tire 202. The information for identifying the tire 202 is, for example, the identifier of the tire sensor 104. The information storage unit 254 may store information for identifying the tire 202 in association with the tire status information.

[0031] The information storage unit 254 may further store vehicle-specific information that indicates the characteristics of each vehicle. The vehicle-specific information may be stored in the information storage unit 254 when the control device 250 is manufactured, or it may be received by the communication control unit 258 via the communication device 270 and stored in the information storage unit 254. An example of vehicle-specific information is information indicating the model number of the vehicle 102, information indicating the unit number of the vehicle 102, information indicating the model number of the tire 202, and location information of the tire 202 associated with information for identifying the tire 202. The location information of the tire 202 may be, for example, information indicating the right front wheel, left rear wheel, right rear wheel, or left front wheel on the vehicle 102.

[0032] The communication control unit 258 transmits tire status information, usage status information, and external factor information stored in the information storage unit 254 from the communication device 270 to the management device 108 or data server 110 for the purpose of causing the management device 108 to generate a learning model or algorithm. The management device 108 generates a learning model or algorithm for identifying the tire status based on the tire status information, usage status information, and external factor information. The management device 108 transmits the learning model or algorithm to the vehicle 102 or vehicle 112. The communication control unit 258 may further transmit vehicle body factor information from the communication device 270 to the management device 108 or data server 110. The management device 108 may further generate a learning model or algorithm for identifying the tire status based on the vehicle body factor information.

[0033] Since usage status information and external factor information are provided to the management device 108 in association with tire status information of the tires 202 of the vehicle 102 equipped with tire sensors 104, the management device 108 can generate a learning model or algorithm that can identify the tire status with high accuracy. Furthermore, by providing vehicle body factor information to the management device 108, the management device 108 can generate a learning model or algorithm that can identify the tire status with even higher accuracy.

[0034] The status identification unit 256 transfers the tire status information stored in the information storage unit 254 to the communication control unit 258 or the output control unit 260 for the purpose of notifying the user of the management device 108 or the operator of the vehicle 102 of the status of the tire 202 measured by the tire sensor 104. The communication control unit 258 causes the communication device 270 to transmit the tire status information to the management device 108 or the data server 110.

[0035] The output control unit 260 causes the output device 280 to output a notification to the operator of the vehicle 102 if the condition of the tire 202, as indicated by the tire condition information, meets a predetermined condition. The predetermined condition may be that the temperature or pressure of the tire 202 exceeds a predetermined threshold for a predetermined period of time. For example, if the temperature of the tire 202 exceeds a temperature that is safe and permissible, the output control unit 260 causes the output device 280 to display, "The tire temperature is high. Please refrain from driving."

[0036] The control device 250 of vehicle 102 not only collects learning data and provides it to the management device 108, but can also detect abnormalities in the condition of the tires 202 of vehicle 102 working at the work site and notify the operator of vehicle 102. The operator of vehicle 102 can quickly recognize that the tires 202 are in a dangerous condition, thus avoiding tire failure.

[0037] Vehicle 102 may be equipped with a tire sensor 104 for a specific period of time. The tire sensor 104 measures the condition of the tire 202 during that specific period. After the specific period, the tire sensor 104 may be removed from vehicle 102. Subsequently, the tire sensor 104 may be attached to a vehicle other than vehicle 102 and measure the condition of the tire on that vehicle. The vehicle 102 and the other vehicle may be vehicles working at the same work site, or vehicles working at different work sites.

[0038] A single tire sensor can collect tire condition information for each tire on different vehicles. Furthermore, a single tire sensor can collect tire condition information for each tire on vehicles working at different work sites. While reducing the costs associated with introducing a TPMS (Tire Pressure Monitoring System), various types of information collected under diverse operating conditions can be provided to the management device 108 as learning data.

[0039] Figure 3 shows the configuration of a vehicle 112 according to this embodiment. The vehicle 112 includes a plurality of tires 202, a plurality of fluid pressure suspensions 204, an engine 206, a cooler 208, a usage state detection device 220, an external factor measurement device 240, a control device 250, a communication device 270, and an output device 280. The control device 250 has an information acquisition unit 252, an information storage unit 254, a state identification unit 257, a communication control unit 258, and an output control unit 260. Components that are denoted by the same reference numerals in Figures 2 and 3 may have the same structure or the same function.

[0040] The communication control unit 258 acquires the learning model or algorithm generated by the management device 108 via the communication device 270 and stores it in the information storage unit 254. The communication control unit 258 may also acquire the learning model or algorithm generated based on external factor information, usage status information, and tire condition information measured at a location other than the vehicle's work site, such as a factory, and store it in the information storage unit 254. The communication control unit 258 may also acquire the learning model or algorithm generated based on virtual data and store it in the information storage unit 254. The communication control unit 258 may acquire the learning model or algorithm generated using external factor information, usage status information, and tire condition information of a vehicle 102, which is different from vehicle 112, as learning data, and store it in the information storage unit 254.

[0041] The status identification unit 257 acquires external factor information, including the outside temperature information of the vehicle 112, and usage status information from the information storage unit 254. Based on the external factor information, including the outside temperature information of the vehicle 112, and the usage status information, the status identification unit 257 identifies the status of the tire 202. The status identification unit 257 may use a learning model or algorithm stored in the information storage unit 254 to identify the status of the tire 202 from the external factor information, including the outside temperature information of the vehicle 112, and the usage status information. The status identification unit 257 may correct the status of the tire 202 based on vehicle body factor information. The learning model or algorithm may be received by the communication device 270, or it may be written directly to the control device 250 before or after the control device 250 is mounted on the vehicle 112.

[0042] The status identification unit 257 transfers estimated tire status information indicating the status of the identified tire 202 to the communication control unit 258 or the output control unit 260. The communication control unit 258 or the output control unit 260 outputs the transferred estimated tire status information. Here, "output" means outputting to an external location of the control device 250, and this concept includes not only visual display or transmission via a communication network, but also handing over the information to various controllers other than the control device 250. The communication control unit 258 causes the communication device 270 to transmit the estimated tire status information transferred from the status identification unit 257 to the management device 108 or the data server 110.

[0043] When the state of the tire 202 indicated by the estimated tire state information specified by the state specifying unit 257 satisfies a predetermined condition, the output control unit 260 causes the output device 280 to output a notification to the operator of the vehicle 112. The predetermined condition may be that the temperature or pressure of the tire 202 continuously exceeds a predetermined threshold value for a predetermined time. For example, when the temperature of the tire 202 exceeds the temperature allowable for safety, the output control unit 260 causes the output device 280 to display "The tire temperature is high. Please refrain from driving."

[0044] According to the present embodiment, even when the tire sensor is not attached to the tire 202 of the vehicle 112, the control device 250 can accurately specify the state of the tire 202 using the learning model or algorithm generated by the management device 108. Further, the control device 250 can accurately specify the state of the tire 202 even when the communication network 106 is out of order.

[0045] As another embodiment, for the purpose of causing the management device 108 to specify the state of the tire 202, the communication control unit 258 may cause the use state information, external factor information, and vehicle body factor information stored in the information storage unit 254 to be transmitted from the communication device 270 to the management device 108 or the data server 110. The management device 108 specifies the state of the tire 202 of the vehicle 112 from the use state information, external factor information, and vehicle body factor information received from the vehicle 112 or the data server 110 using the learning model or algorithm generated by the management device 108. The management device 108 transmits tire state information indicating the state of the tire 202 of the vehicle 112 to the vehicle 112.

[0046] The communication control unit 258 transfers the estimated tire state information received from the management device 108 via the communication device 270 to the output control unit 260. When the state of the tire 202 indicated by the estimated tire state information specified by the management device 108 satisfies a predetermined condition, the output control unit 260 causes the output device 280 to output a notification to the operator of the vehicle 112. The output device 280 is, for example, a display device that displays the notification on the screen. The output device 280 may be an audio output device that outputs the notification by voice.

[0047] When the state of the tire 202 indicated by the estimated tire state information specified by the management device 108 satisfies a predetermined condition, the output control unit 260 may cause the output device 280 to output a control command for the vehicle 112. The output device 280 may be a control controller that controls the vehicle 112. The control command is, for example, a control command for changing the maximum vehicle speed set in the vehicle 112 or the traveling speed of the vehicle 112 during traveling. The control command may be a control command for reducing the maximum vehicle speed set in the vehicle 112, or a control command for decelerating the vehicle 112 during traveling.

[0048] Even when the state specifying unit 257 of the vehicle 112 does not have a function of specifying the state of the tire using learning data or an algorithm, an abnormality in the state of the tire 202 of the vehicle 112 can be detected with high accuracy and notified to the operator of the vehicle 112. Further, since the management device 108 specifies the state of the tire 202, the computational load on the control device 250 of the vehicle 112 is reduced.

[0049] FIG. 4 shows the configuration of the management device 108 according to the present embodiment. The management device 108 includes a communication unit 310, an input unit 330, an information acquisition unit 352, an information storage unit 354, a state specifying unit 356, and a model generation unit 320. Each of the information acquisition unit 352, the information storage unit 354, and the state specifying unit 356 may have the same functions as the information acquisition unit 252, the information storage unit 254, and the state specifying unit 257.

[0050] First, the operation of the management device 108 in which it generates a learning model or algorithm for identifying the tire status based on various information including tire status information will be explained. The communication unit 310 receives tire status information, usage status information, external factor information, and vehicle body factor information from one or more vehicles or the data server 110. The communication unit 310 may receive various information collected from one or more vehicles, including vehicle 102, or it may receive virtual various information. The information acquisition unit 352 acquires the tire status information, usage status information, external factor information, and vehicle body factor information received by the communication unit 310, associates them, and stores them in the information storage unit 354.

[0051] The communication unit 310 receives weather information associated with the vehicle's location and time stored in the information storage unit 354 from a database that stores past weather information. The information acquisition unit 352 acquires the weather information received by the communication unit 310 and stores it in the information storage unit 354 in association with the vehicle's location and time. Weather information is information that indicates weather or climate, such as temperature, humidity, atmospheric pressure, rainfall, wind direction, wind speed, or illuminance. Weather information is an example of external factor information.

[0052] The data server 110 may store external factor information, such as identification information of the mine or road, or road surface information, associated with location and time. The communication unit 310 receives the external factor information associated with location and time stored in the information storage unit 354 from the data server 110. The information acquisition unit 352 acquires the external factor information received by the communication unit 310 and stores it in the information storage unit 354, associated with the vehicle's location and time.

[0053] The input unit 330 receives input of virtual vehicle usage status information, external factor information, and vehicle body factor information. The information acquisition unit 352 acquires the virtual vehicle usage status information, external factor information, and vehicle body factor information input to the input unit 330, associates them, and stores them in the information storage unit 354.

[0054] The model generation unit 320 generates a learning model or algorithm for identifying the tire condition based on the tire condition information, usage condition information, external factor information, and vehicle body factor information stored in the information storage unit 354. The model generation unit 320 may generate a learning model or algorithm based on various information, including tire condition information collected by at least one vehicle, including vehicle 102, or it may generate a learning model or algorithm based on various information, including tire condition information of a virtual vehicle. The model generation unit 320 stores the learning model or algorithm in the information storage unit 354. The model generation unit 320 transmits the learning model or algorithm from the communication unit 310 to vehicle 102 or vehicle 112. An example of an algorithm is regression analysis.

[0055] The model generation unit 320 may create a learning model or algorithm for each vehicle body factor information. For example, the model generation unit 320 may create a learning model or algorithm for each tire position or for each vehicle body model.

[0056] The model generation unit 320 generates a learning model or algorithm using weather information as training data, enabling high-precision identification of the tire condition of vehicles working in various regions or seasons. Furthermore, the model generation unit 320 can identify the tire condition with even greater precision by creating a learning model or algorithm for each tire position or for each vehicle model.

[0057] Next, the operation of the management device 108 to identify the state of the vehicle 112's tires 202 based on various information acquired by the vehicle 112 will be described. The communication unit 310 receives usage status information, external factor information, and vehicle body factor information from the data server 110 or the vehicle 112. The information acquisition unit 352 acquires the usage status information, external factor information, and vehicle body factor information of the vehicle 112 received by the communication unit 310, associates them, and stores them in the information storage unit 354.

[0058] The status identification unit 356 uses a learning model or algorithm stored in the information storage unit 354 to identify the status of the vehicle 112's tires 202 from the vehicle 112's usage status information, external factor information, and vehicle body factor information stored in the information storage unit 354. The status identification unit 356 causes the output unit 340 to output a notification regarding the status of the vehicle 112's tires 202 to the user of the management device 108. Here, "output" means outputting to an external location of the management device 108, and this concept includes not only visual display or transmission via a communication network, but also handing over to various controllers other than the management device 108. For example, a report is created and displayed indicating that the temperature or pressure of the vehicle 112's tires 202 exceeds a predetermined temperature or pressure.

[0059] The status identification unit 356 causes the communication unit 310 to output a notification regarding the status of the vehicle's tires 202 to the vehicle 112. The vehicle's control device 250 displays the notification regarding the status of the tires 202 to the operator of the vehicle 112 via the output device 280.

[0060] Even if the vehicle 112's control device 250 does not have a function to identify the condition of the tires, the management device 108 can identify the condition of the vehicle 112's tires 202 with high accuracy. Furthermore, it can notify the user of the management device 108 and the operator of the vehicle 112 of any abnormality in the tires 202.

[0061] Next, the operation by which the management device 108 notifies the user of the management device 108 based on the estimated tire condition information acquired from the vehicle 112 will be described. The communication unit 310 receives estimated tire condition information from the vehicle 112, indicating the condition of the tires 202 identified by the vehicle 112. The communication unit 310 transfers the estimated tire condition information to the information storage unit 354 via the information acquisition unit 352. The output unit 340 displays the notification regarding the condition of the vehicle 112's tires 202, stored in the information storage unit 354, to the user of the management device 108. For example, the output unit 340 creates and displays a report indicating that the temperature or pressure of the vehicle 112's tires 202 exceeds a predetermined temperature or pressure.

[0062] The communication unit 310 may transmit a notification regarding the status of the vehicle's tires 202 to the vehicle 112. The control device 250 of the vehicle 112 may display the notification regarding the status of the vehicle's tires 202 to the operator of the vehicle 112 via the output device 280.

[0063] The management device 108 can centrally manage the tire status of numerous vehicles working at each of multiple work sites. This allows the user of the management device 108 to grasp statistical data on the tire status of numerous vehicles at multiple work sites. Furthermore, the user of the management device 108 can consider improving the training data or algorithm based on the large amount of statistical data.

[0064] Next, the operation of the management device 108 in which it performs a simulation of the vehicle's tire condition based on various information virtually created by the user will be explained. The input unit 330 receives input of virtual vehicle usage status information, external factor information, and vehicle body factor information. The information acquisition unit 352 acquires the virtual vehicle usage status information, external factor information, and vehicle body factor information input to the input unit 330, associates them, and stores them in the information storage unit 354.

[0065] The status identification unit 356 identifies the state of the tires of a virtual vehicle based on the virtual vehicle usage status information, external factor information, and vehicle body factor information stored in the information storage unit 354. The virtual vehicle usage status information, external factor information, and vehicle body factor information may all be virtual information, or only some of them may be virtual information. For example, the status identification unit 356 identifies the state of the vehicle's tires based on virtual climate and virtual usage status, as well as actual location and actual vehicle model information. The status identification unit 356 outputs the tire state from the output unit 340.

[0066] The control device 108 can perform simulations of tire conditions under future work site climate and vehicle usage conditions. For example, it can use a learning model or algorithm created based on various information acquired over one month in winter to estimate the tire condition of a vehicle if work is carried out in the summer.

[0067] Figure 5 shows an example of a learning model for identifying the condition of a tire. The target variable of the learning model is tire condition information indicating at least one of the temperature and pressure of the tire 202. The explanatory variables of the learning model are vehicle body factor information, usage condition information, and external factor information. The model generation unit 320 generates a learning model by learning the vehicle body factor information, usage condition information, external factor information, and tire condition information of the vehicle 102 as learning data.

[0068] One of the explanatory variables, vehicle-related information, includes information indicating the model number of vehicle 102, information indicating the unit number of vehicle 102, information indicating the model number of tire 202, and location information of tire 202. Another explanatory variable, usage status information, includes SMR, continuous operating time, cumulative TKPH (Tonne Kilometre Per Hour) during continuous operating time, cumulative distance traveled during continuous operating time, cumulative ambient temperature during continuous operating time, and cumulative engine speed of engine 206 during continuous operating time. Another explanatory variable, external factor information, includes ambient temperature, climate information such as temperature, humidity, atmospheric pressure, rainfall, wind direction, wind speed, or illuminance, time of day such as date, hour, and month, location information such as latitude, longitude, and altitude, identification information of the mine or road, and information on the road surface conditions of the road, such as roughness, road surface severity, type of mine such as iron or copper, and gradient. TKPH is the product of the total mass of the vehicle 102, including the mass of the loaded cargo, and the speed of the vehicle 102, and is an example of usage status information.

[0069] Due to heat conduction between the tire 202 and the outside air, the temperature of the tire 202 fluctuates with the outside air temperature. Therefore, the temperature of the tire 202 is correlated with the outside air temperature. Factors that increase the temperature of the tire 202, other than rising outside air temperature, include heat generated by internal friction of the tire 202 and heat generated by the engine 206. Factors that decrease the temperature of the tire 202, other than falling outside air temperature, include heat absorption by the outside air.

[0070] The heat generated by internal friction in tire 202 is due to internal friction of the rubber material in the tread and sidewall portions of tire 202. The rubber material is compressed when in contact with the road surface and returns to its original shape when not in contact. This expansion and contraction causes the rubber material in the tread and sidewall portions to flex, creating friction within the rubber material and generating frictional heat. This frictional heat is conducted, causing the temperature of tire 202 to rise.

[0071] The amount of heat generated by internal friction in the tire 202 can be calculated from the magnitude of expansion and contraction of the rubber material and the frequency of expansion and contraction of the rubber material. The larger the total mass of the vehicle 102, including the mass of the loaded cargo, the greater the expansion and contraction, and therefore the greater the amount of heat generated. The total mass of the vehicle 102 can be calculated based on the pressure of the fluid-pressure suspension 204. Therefore, the temperature of the tire 202 is correlated with the pressure of the fluid-pressure suspension 204. Also, the higher the speed of the vehicle 102, the higher the frequency of expansion and contraction, and therefore the greater the amount of heat generated. Therefore, the temperature of the tire 202 is correlated with the speed of the vehicle 102. Consequently, the temperature of the tire 202 is also correlated with TKPH, which is the product of the total mass of the vehicle 102 and the speed of the vehicle 102.

[0072] The heat generated by the engine 206 is conducted, causing the temperature of the tire 202 to rise. The higher the rotational speed of the engine 206, the greater the amount of heat generated by the engine 206, and therefore the greater the temperature of the tire 202 rises. The heat generated by the coolant in the radiator 208 is conducted, causing the temperature of the tire 202 to rise. The higher the temperature of the coolant in the radiator 208, the greater the amount of heat generated by the coolant in the radiator 208, and therefore the greater the temperature of the tire 202 rises. Specifically, the heat generated by the engine 206 is conducted, causing the temperature of the coolant in the radiator 208 to rise. The heat generated by the high-temperature coolant in the radiator 208 is conducted to the tire 202 by the airflow from the fan connected to the engine 206, causing the temperature of the tire 202 to rise. Therefore, the temperature of the tire 202 is correlated with the strength of the fan's airflow. The strength of the fan's airflow can be calculated based on the fan's rotational speed. If the fan's rotational speed is proportional to the engine 206's rotational speed, the fan's rotational speed can be calculated from the engine 206's rotational speed. Therefore, the temperature of the tire 202 is correlated with the rotational speed of the engine 206 and the temperature of the coolant in the cooler 208.

[0073] Heat absorption by the outside air is due to heat conduction between the tire 202 and the outside air. The amount of heat absorbed by the outside air can be calculated based on the temperature difference between the temperature of the tire 202 and the outside air. Furthermore, since the amount of heat absorbed by the outside air increases as the speed of the vehicle 102 increases, the calculated amount of heat absorbed can be corrected based on the speed of the vehicle 102. Therefore, the temperature of the tire 202 is correlated with the speed of the vehicle 102 and the temperature difference between the temperature of the tire 202 and the outside air.

[0074] There is a correlation between the temperature of tire 202 and the pressure of tire 202. Therefore, the pressure of tire 202 is correlated with the following explanatory variables, which are correlated with the temperature of tire 202: ambient temperature, pressure of the fluid-pressure suspension 204, speed of vehicle 102, TKPH, rotational speed of engine 206, and temperature of the coolant in the cooler 208.

[0075] The model generation unit 320 generates a learning model using explanatory variables that have a high correlation with the target variable, the temperature or pressure of the tire 202, as training data. Therefore, the model generation unit 320 can generate a learning model that accurately identifies the temperature or pressure of the tire 202. Tire conditions vary depending on the road surface conditions of the mine or road, but since the model generation unit 320 uses the road surface conditions as training data to generate the learning model, the generated learning model can be applied to different roads.

[0076] Figure 6 shows an example of the processing flow of the control device 250 according to this embodiment. In step 500, the information acquisition unit 252 acquires ambient temperature information indicating the ambient temperature and stores it in the information storage unit 254. In step 502, the information acquisition unit 252 acquires usage status information indicating the usage status of the vehicle 112 and stores it in the information storage unit 254.

[0077] In step 504, the status identification unit 257 identifies the status of the tire 202 based on the outside temperature information and usage status information stored in the information storage unit 254. In step 506, the output control unit 260 outputs a notification regarding the status of the tire 202 to the operator of the vehicle 112 via the output device 280. In step 508, the communication control unit 258 transmits estimated tire status information indicating the status of the tire 202 from the communication device 270 to the management device 108 or the data server 110.

[0078] Figure 7 shows an example of a computer 1200 in which this embodiment may be embodied in whole or in part. A program installed on the computer 1200 can cause the computer 1200 to function as an operation or one or more sections of the apparatus according to this embodiment, or to execute such operation or one or more sections, and / or to cause the computer 1200 to execute a process or a stage of such process according to this embodiment. Such a program may be executed by the CPU 1212 to cause the computer 1200 to perform a specific operation associated with some or all of the blocks of the flowcharts and configuration diagrams described herein.

[0079] The computer 1200 according to this embodiment includes a CPU 1212, RAM 1214, a graphics controller 1216, and a display device 1218, which are interconnected by a host controller 1210. The computer 1200 includes a communication interface 1222, a storage device 1224 such as a hard disk drive, an input / output unit such as a DVD-ROM drive 1226, and an IC card drive, which are connected to the host controller 1210 via an input / output controller 1220. The computer also includes legacy input / output units such as a ROM 1230 and a keyboard 1242, which are connected to the input / output controller 1220 via an input / output chip 1240.

[0080] The CPU 1212 operates according to the programs stored in the ROM 1230 and RAM 1214, thereby controlling each unit. The graphics controller 1216 acquires image data generated by the CPU 1212 from the frame buffer provided in the RAM 1214 or from itself, and displays the image data on the display device 1218.

[0081] The communication interface 1222 communicates with other electronic devices via a network. The storage device 1224 stores programs and data used by the CPU 1212 in the computer 1200. The DVD-ROM drive 1226 reads programs or data from the DVD-ROM 1227 and provides them to the storage device 1224 via the RAM 1214. The IC card drive reads programs and data from the IC card and / or writes programs and data to the IC card.

[0082] The ROM 1230 stores boot programs and / or programs that depend on the computer 1200's hardware, which are executed by the computer 1200 when activated. The input / output chip 1240 may connect various input / output units to the input / output controller 1220 via a parallel port, serial port, keyboard port, mouse port, etc.

[0083] The program is provided on a computer-readable medium such as a DVD-ROM 1227 or an IC card. The program is read from the computer-readable medium and installed on a storage device 1224, RAM 1214, or ROM 1230, which are examples of computer-readable mediums, and executed by the CPU 1212. The information processing described within these programs is read by the computer 1200, resulting in coordination between the program and the various types of hardware resources described above. The apparatus or method may be configured to realize the manipulation or processing of information in accordance with the use of the computer 1200.

[0084] For example, when communication is performed between a computer 1200 and an external device, the CPU 1212 may execute a communication program loaded into the RAM 1214 and, based on the processing described in the communication program, instruct the communication interface 1222 to perform communication processing. Under the control of the CPU 1212, the communication interface 1222 reads transmission data stored in a transmission buffer processing area provided in a recording medium such as the RAM 1214, storage device 1224, DVD-ROM 1227, or IC card, transmits the read transmission data to the network, or writes received data received from the network to a receive buffer processing area provided on the recording medium.

[0085] The CPU 1212 may read all or necessary parts of a file or database stored on an external recording medium such as a storage device 1224, a DVD-ROM drive 1226 (DVD-ROM 1227), or an IC card into the RAM 1214, and perform various types of processing on the data in the RAM 1214. The CPU 1212 then writes the processed data back to the external recording medium.

[0086] Various types of information, such as various types of programs, data, tables, and databases, may be stored on the recording medium and subjected to information processing. The CPU 1212 may perform various types of processing on the data read from the RAM 1214, including various types of operations, information processing, conditional judgments, conditional branching, unconditional branching, information retrieval / replacement, etc., as described throughout this disclosure and specified by the program instruction sequence, and write the results back to the RAM 1214. The CPU 1212 may search for information in files, databases, etc., within the recording medium. For example, if a plurality of entries having attribute values ​​of a first attribute, each associated with an attribute value of a second attribute, are stored in the recording medium, the CPU 1212 may search among the plurality of entries for an entry that matches the condition for which the attribute value of the first attribute is specified, read the attribute value of the second attribute stored in that entry, and thereby obtain the attribute value of the second attribute associated with the first attribute that satisfies a predetermined condition.

[0087] The programs or software modules described above may be stored on or near the computer 1200 on a computer-readable medium. A recording medium such as a hard disk or RAM provided within a server system connected to a dedicated communication network or the Internet can be used as a computer-readable medium, thereby providing the programs to the computer 1200 via the network.

[0088] Although the invention has been described using embodiments, the technical scope of the present invention is not limited to the scope described in the embodiments above. It will be apparent to those skilled in the art that various modifications or improvements can be made to the embodiments described above. It will be clear from the claims that such modified or improved forms may also be included in the technical scope of the present invention.

[0089] It should be noted that the execution order of operations, procedures, steps, and stages in the devices, systems, programs, and methods shown in the claims, specifications, and drawings is not explicitly stated as "before" or "prior to," and can be implemented in any order unless the output of a previous process is used in a later process. Even if the operation flow in the claims, specifications, and drawings is described using phrases such as "first," "next," etc., for convenience, this does not mean that it is mandatory to perform the operations in that order.

[0090] 100 Vehicle management system, 102 Vehicle, 104 Tire sensor, 106 Communication network, 108 Management device, 110 Data server, 112 Vehicle, 202 Tire, 204 Fluid pressure suspension, 206 Engine, 208 Cooler, 220 Usage status detection device, 224 Pressure sensor, 226 Rotation sensor, 228 Cooler temperature sensor, 230 Speed ​​sensor, 232 Odometer, 234 Timer, 240 External factor measurement device, 242 Outside temperature sensor, 244 Clock, 246 Position sensor, 250 Control device, 252 Information acquisition unit, 254 Information storage unit, 256 Status identification unit, 257 Status identification unit, 258 Communication control unit, 260 Output control unit, 270 Communication device, 280 Output device, 310 Communication unit, 320 Model generation unit, 330 Input unit, 340 Output unit, 352 Information acquisition unit, 354 Information storage unit, 356 State identification unit, 1200 Computer, 1210 Host controller, 1212 CPU, 1214 RAM, 1216 Graphics controller, 1218 Display device, 1220 Input / output controller, 1222 Communication interface, 1224 Storage device, 1226 DVD-ROM drive, 1227 DVD-ROM, 1230 ROM, 1240 Input / output chip, 1242 Keyboard

Claims

1. A tire condition identification system comprising at least one processor, wherein the at least one processor acquires ambient temperature information indicating the ambient temperature of the vehicle and usage status information indicating the usage status of the vehicle, identifies the condition of the tires on the vehicle based on the ambient temperature information and the usage status information, and outputs tire condition information indicating the condition of the tires.

2. The tire condition identification system according to claim 1, wherein the at least one processor identifies the temperature of the tire based on the ambient temperature information and the usage status information, and outputs the tire condition information indicating the temperature of the tire.

3. The tire condition identification system according to claim 1, wherein the at least one processor identifies the pressure of the tire based on the ambient temperature information and the usage status information, and outputs the tire condition information indicating the pressure of the tire.

4. The tire condition identification system according to claim 1, wherein the usage status information includes information indicating the operating time of the vehicle.

5. The tire condition identification system according to claim 1, wherein the usage status information includes information indicating the continuous operating time, which is the time the vehicle is in continuous operation.

6. The tire condition identification system according to claim 1, wherein the usage condition information includes information indicating the load on the tires of the vehicle.

7. The tire condition identification system according to claim 6, wherein the information indicating the load includes information indicating the mass of the vehicle and the load loaded on the vehicle.

8. The tire condition identification system according to claim 1, wherein the usage status information includes information indicating the distance traveled by the vehicle.

9. The tire condition identification system according to claim 1, wherein the usage status information includes information indicating the speed of the vehicle.

10. The tire condition identification system according to any one of claims 1 to 9, wherein the at least one processor causes an output device to output a notification when the condition of the tire indicated by the tire condition information satisfies predetermined conditions.

11. The tire condition identification system according to claim 10, wherein the predetermined condition includes the temperature or pressure of the tire continuously exceeding a predetermined threshold for a predetermined period of time.

12. The tire condition identification system according to any one of claims 1 to 9, wherein the at least one processor uses a learning model generated with respect to ambient temperature information, usage status information, and tire condition information as learning data to identify the condition of the tires provided by the vehicle from the ambient temperature information and usage status information of the vehicle.

13. The tire condition identification system according to claim 12, wherein the at least one processor uses the learning model generated as learning data the ambient temperature information, usage status information, and tire condition information of a second vehicle other than the first vehicle, which is the vehicle, to identify the condition of the tires of the first vehicle from the ambient temperature information and usage status information of the first vehicle.

14. A vehicle comprising a tire, an ambient temperature sensor for measuring the ambient temperature of the vehicle, a detection device for detecting the usage status of the vehicle, and a tire condition identification system according to any one of claims 1 to 7.

15. A vehicle management system comprising the vehicle and the tire condition identification system according to any one of claims 1 to 9.

16. The vehicle management system according to claim 15, further comprising a second vehicle separate from the first vehicle, wherein the at least one processor uses a learning model generated as learning data, which includes ambient temperature information indicating the ambient temperature of the second vehicle, usage status information indicating the usage status of the second vehicle, and tire status information indicating the condition of the tires of the second vehicle, to identify the condition of the tires of the first vehicle from the ambient temperature information and usage status information of the first vehicle.

17. The vehicle management system according to claim 16, wherein the first vehicle comprises the tire, a first ambient temperature sensor for measuring the ambient temperature of the first vehicle, and a first detection device for detecting the usage status of the first vehicle, and the second vehicle comprises the tire, a second ambient temperature sensor for measuring the ambient temperature of the second vehicle, a second detection device for detecting the usage status of the second vehicle, and a tire sensor for measuring the condition of the tire of the second vehicle, and the at least one processor uses a learning model generated as learning data, which includes ambient temperature information indicating the ambient temperature measured by the second ambient temperature sensor, usage status information indicating the usage status detected by the second detection device, and tire status information indicating the condition of the tire measured by the tire sensor, to identify the condition of the tire of the first vehicle from the ambient temperature information and usage status information of the first vehicle.

18. A program for causing a computer to function as a tire condition identification system according to any one of claims 1 to 7.

19. A method for determining tire condition, comprising: acquiring ambient temperature information indicating the ambient temperature of a vehicle and usage status information indicating the usage status of the vehicle; determining the condition of the tires equipped on the vehicle based on the ambient temperature information and the usage status information; and outputting tire condition information indicating the condition of the tires.

20. A method for identifying the tire condition according to claim 19, comprising generating a learning model using ambient temperature information indicating the ambient temperature of a second vehicle other than the first vehicle, usage status information indicating the usage status of the second vehicle, and tire condition information indicating the condition of the tires of the second vehicle as learning data, and using the learning model to identify the condition of the tires of the first vehicle from the ambient temperature information and usage status information of the first vehicle.

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