Abstract: A vehicle control device includes a processor and memory. The memory stores relation-defining data for defining a relation between a state of a vehicle and an action variable that is a variable relating to operations of a transmission installed in the vehicle. The processor is configured to execute acquisition processing, operation processing, reward calculation processing, updating processing, counting processing, and limiting processing. The processor is configured to output the relation-defining data updated so that an expected income is increased when the transmission is operated following the relation-defining data, based on an updating map.

Abstract: A degradation estimation device includes a storage device and an execution device. The storage device is configured to store mapping data that defines a map that outputs an output variable indicating a degree of degradation of a seal member when an input variable is input. The map includes a thermal history variable and a load history variable as the input variable. The thermal history variable is a variable indicating a period during which the seal member has been exposed to a temperature within a predetermined temperature range. The load history variable is a variable indicating the number of times a load has acted on the seal member. The execution device is configured to perform an acquisition process of acquiring the input variable and a calculation process of outputting a value of the output variable by inputting the input variable acquired in the acquisition process to the map.

Abstract: An anomaly determination apparatus for a vehicle that includes a transmission includes an execution device and a memory device. The memory device is configured to store map data that defines pre-trained map, which has been trained through machine learning. When a variable representing time-series data of a rotation speed of a gear is fed to the map as an input variable, the map outputs a state variable representing a state of the gear as an output variable. The execution device is configured to execute: an obtaining process that obtains the variable representing the time-series data as a value of the input variable; and a determination process that determines whether there is an anomaly in the transmission based on a value of the output variable that is output by the map when the value of the input variable is fed to the map.

Abstract: The vehicle evaluation system includes processing circuitry 110 and a storage device 120. The storage device 120 stores data of a learned model that has been trained to generate reference operation data from training sound data. The processing circuitry 110 is configured to execute a generation process and an evaluation process. The generation process is a process that generates generated data, which is data in an operation status, by inputting, to the learned model, evaluation sound data recorded while operating the target vehicle 10 for a predetermined period of time. The evaluation process is a process that compares target operation data, which indicates the operation status of the target vehicle collected simultaneously with the evaluation sound data, with the generated data to evaluate the target vehicle 10 based on the magnitude of deviation between them.

Abstract: A vehicle evaluation system includes processing circuitry and a memory device. The memory device stores data of a pretrained model. The pretrained model is a model trained by supervised learning to generate operation data from training sound data. The operation data is data indicating changes in operation information in a measurement operation pattern. The processing circuitry is configured to perform a generation process and an evaluation process. The generation process is a process of outputting generated data which is data of operation information generated by inputting the evaluation data to the pretrained model. The evaluation data includes evaluation sound data recorded while operating a target vehicle in the measurement operation pattern. The evaluation process is a process of comparing the operation data with the generated data and evaluating the target vehicle in accordance with the magnitude of a difference therebetween.

Abstract: A storage device stores a mapping data entry that specifies a mapping and includes data learned through machine learning. A detection value of an oil temperature sensor is an oil temperature detection value. When oil temperature relation data, which is data corresponding to time series data of the oil temperature detection value, is input to the mapping as an input variable, the mapping outputs an output variable that determines whether a frictional engagement element has an anomaly. Processing circuitry executes an obtainment process that obtains the input variable and an anomaly determination process that determines whether the frictional engagement element has an anomaly based on the output variable that is output from the mapping as a result of inputting the input variable obtained in the obtainment process into the mapping.

Abstract: A diagnostic apparatus for a vehicle provided with a continuously-variable transmission including a primary pulley, a secondary pulley and a belt looped over the primary and secondary pulleys, such that each of the primary and secondary pulleys includes a hydraulic actuator to which a working fluid is to be supplied. The diagnostic apparatus is configured, in event of occurrence of slippage of the belt on at least one of the primary and secondary pulleys, to infer a factor causing the slippage of the belt, based on at least one of a hydraulic pressure of the working fluid supplied to the hydraulic actuator of the primary pulley and a hydraulic pressure of the working fluid supplied to the hydraulic actuator of the secondary pulley, upon the occurrence of the slippage of the belt.

Abstract: A hydraulic pressure calculation apparatus is applied to a gear shifting system including a transmission configured to switch between a connected state and a disconnected state of a friction engagement element depending on a hydraulic pressure supplied from a hydraulic circuit, and a hydraulic controller configured to control the hydraulic circuit. The hydraulic pressure calculation apparatus includes a memory and a processor. The memory stores pieces of mapping data of a plurality of phases obtained by dividing a period from a start to an end of switching between the connected state and the disconnected state of the friction engagement element. Each piece of the mapping data defines a mapping. The processor is configured to output, as an output variable, an estimated hydraulic pressure variable indicating an estimated value of an actual hydraulic pressure supplied from the hydraulic circuit to the friction engagement element.

Abstract: A heat load estimation device for a friction engaging element that estimates a heat load when at least one of a temperature, a heat generation amount, and presence or absence of seizure in the friction engaging element at a time of shifting of the transmission is regarded as the heat load, includes a storage device and an execution device. The storage device stores mapping data defining mapping. The mapping includes, as an input variable, a speed variable that is a variable indicating a relative rotation speed of members of the friction engaging element and a hydraulic pressure variable that is a variable indicating hydraulic pressure during the shifting of the transmission, and includes, as an output variable, the heat load. The execution device executes a calculation process for calculating a value of the output variable and a change process for changing an execution mode of the calculation process.

Abstract: A control device serving as a torque estimation device includes a storage device and a processing circuit. The storage device stores data of a trained neural network. The trained neural network is trained using training data including data of an actually-measured torque that is measured, data of an accelerator operation amount in a period of a predetermined length up to a time point of measurement of the actually-measured torque, and data of an acceleration of a vehicle from the time point of measurement of the actually-measured torque onward. The processing circuit inputs, to the trained neural network stored in the storage device, input data including the data of the accelerator operation amount and the data of the acceleration of the vehicle, to estimate a torque generated in a power transmission member.

Abstract: A vehicle control device includes: a storage device that stores relation-defining data that is data for defining a relation between a state of a vehicle and an action variable; and an executing device configured to acquire the state, operate a drivetrain device based on a value of the action variable, derive a reward such that the reward is larger when the state of the drivetrain device based on the acquired state satisfies a predetermined criterion, perform an updating of the relation-defining data using an updating map, and restrict the updating of the relation-defining data such that an updating amount of the relation-defining data is smaller when the drivetrain device is subject to a predetermined restriction.

Abstract: An oil pressure learning method of an automatic transmission includes acquiring a state of a vehicle in a state where relational regulation data is stored, supplying oil to the automatic transmission such that the value of the oil pressure is set to an oil pressure command value, calculating, as a specific variable, a variable representing an amount in which a detected input rotation speed exceeds a target input rotation speed, or the like, calculating a reward in a manner in which it has a larger value when the specific variable satisfies a criterion than when it does not satisfy the criterion, updating the relational regulation data by inputting, to an update mapping, the reward and the oil pressure command value, and calculating a torque variable having a value that is increased as an amount of change in an input torque is increased.

Abstract: A control device serving as a torque estimation device includes a storage device and a processing circuit. The storage device stores data of a trained neural network. The trained neural network is trained using training data including data of an actually-measured torque that is measured, data of an accelerator operation amount in a period of a predetermined length up to a time point of measurement of the actually-measured torque, and data of an acceleration of a vehicle from the time point of measurement of the actually-measured torque onward. The processing circuit inputs, to the trained neural network stored in the storage device, input data including the data of the accelerator operation amount and the data of the acceleration of the vehicle, to estimate a torque generated in a power transmission member.

Abstract: A device for a vehicle including a power transfer device, the power transfer device having an input pulley, an output pulley, and an endless rotary member, the device including: a memory configured to store mapping data that include data that prescribe mapping that represents correspondence between an input variable and an output variable, the data being learned through machine learning, the input variable being at least one of input rotational speed-related data, and output rotational speed-related data, the output variable specifying whether an abnormality is caused in the endless rotary member; and a processor configured to acquire the input variable, acquire the output variable corresponding to the input variable using the mapping data, and determine, based on the output variable, whether an abnormality is caused in the endless rotary member.

Abstract: A heat load estimation device for a friction engaging element that estimates a heat load when at least one of a temperature, a heat generation amount, and presence or absence of seizure in the friction engaging element at a time of shifting of the transmission is regarded as the heat load, includes a storage device and an execution device. The storage device stores mapping data defining mapping. The mapping includes, as an input variable, a speed variable that is a variable indicating a relative rotation speed of members of the friction engaging element and a hydraulic pressure variable that is a variable indicating hydraulic pressure during the shifting of the transmission, and includes, as an output variable, the heat load. The execution device executes a calculation process for calculating a value of the output variable and a change process for changing an execution mode of the calculation process.

Abstract: A hydraulic pressure calculation apparatus is applied to a gear shifting system including a transmission configured to switch between a connected state and a disconnected state of a friction engagement element depending on a hydraulic pressure supplied from a hydraulic circuit, and a hydraulic controller configured to control the hydraulic circuit. The hydraulic pressure calculation apparatus includes a memory and a processor. The memory stores pieces of mapping data of a plurality of phases obtained by dividing a period from a start to an end of switching between the connected state and the disconnected state of the friction engagement element. Each piece of the mapping data defines a mapping. The processor is configured to output, as an output variable, an estimated hydraulic pressure variable indicating an estimated value of an actual hydraulic pressure supplied from the hydraulic circuit to the friction engagement element.

Abstract: An anomaly determination apparatus for a vehicle that includes a transmission includes an execution device and a memory device. The memory device is configured to store map data that defines pre-trained map, which has been trained through machine learning. When a variable representing time-series data of a rotation speed of a gear is fed to the map as an input variable, the map outputs a state variable representing a state of the gear as an output variable. The execution device is configured to execute: an obtaining process that obtains the variable representing the time-series data as a value of the input variable; and a determination process that determines whether there is an anomaly in the transmission based on a value of the output variable that is output by the map when the value of the input variable is fed to the map.

Abstract: A storage device stores a mapping data entry that specifies a mapping and includes data learned through machine learning. A detection value of an oil temperature sensor is an oil temperature detection value. When oil temperature relation data, which is data corresponding to time series data of the oil temperature detection value, is input to the mapping as an input variable, the mapping outputs an output variable that determines whether a frictional engagement element has an anomaly. Processing circuitry executes an obtainment process that obtains the input variable and an anomaly determination process that determines whether the frictional engagement element has an anomaly based on the output variable that is output from the mapping as a result of inputting the input variable obtained in the obtainment process into the mapping.

Abstract: An abnormality determination device is applied to a vehicle provided with a transmission configured to transmit power by rotation of a shaft. The abnormality determination device includes a processor and a memory. The memory configured to store mapping data that is data that defines mapping learned by machine learning. The processor is configured to execute an acquisition process and a determination process. The acquisition process is a process of acquiring a variable indicating a time-series data of a rotation speed of the shaft and using the variable as a value of an input variable of the mapping. The determination process is a process of determining whether an abnormality has occurred in the transmission based on a value of the output variable acquired using the value of the input variable and the mapping.

Abstract: A gear-shift control data generation method executed by an execution device in a state where relational regulation data used for regulating a relationship between a state of a vehicle and an action variable associated with an operation of a transmission is stored includes a process for acquiring the vehicle state, a process for operating the transmission, a process for assigning, based on the vehicle state, a higher reward when a characteristic of the vehicle satisfies a criterion than when the characteristic does not satisfy the criterion, and a process for updating the relational regulation data by inputting, to an update mapping, the vehicle state, a value of the action variable, and a reward corresponding to the operation. The update mapping outputs the relational regulation data that is updated to increase an expected profit for the reward when the transmission is operated according to the relational regulation data.