Toyota Jidosha Kabushiki Kaisha

Ken Imamura

Atsushi Tabata

Koichi Okuda

Kota Fujii

Hideaki Bunazawa

Keita Sasaki

Atsushi Honda

Jun Yoshida

Hitoshi Matsunaga

Masato Nakano

Shinichi Ito

Toshiaki Tamachi

A training method includes: a simulation step outputting, by a simulator, a characteristic variable based on an input parameter set, the parameter set being input to the simulator and indicating that a specific component is presumed to have an abnormality in advance; and a training step updating, by a training device, mapping based on an input training data and an input teaching data, the input variables being input to the training device as the training data, the input variables including the characteristic variable output in the simulation step, the abnormality determination variable being input to the training device as the teaching data, the abnormality determination variable indicating that the specific component has the abnormality.

Method for training a mapping for outputting an abnormality determination variable for a specific component mounted on a vehicle

A plurality of driving force transmitting components of the same kind is categorized into a plurality of groups depending on a frequency range with the loudest operation sound. A component selection device stores mapping data that is data that defines mapping learned by machine learning. When the user-related information is input as an input variable, the mapping outputs a value corresponding to the input variable as an output variable. The vehicle component selection method causes the component selection method to execute: an input process inputting the user-related information into the mapping as the input variable; a selection process selecting the group corresponding to the output variable output by the mapping from the groups; and a determination process determining the driving force transmitting component categorized into the group selected in the selection process as a component to be installed in the vehicle for the user identified by the user-related information.

Vehicle component selection method

A deterioration estimation device includes a storage device and an execution device. The storage device is configured to store mapping data defining a mapping that outputs an output variable indicating the degree of deterioration of oil when an input variable is input. The mapping includes, as the input variable, a color variable that is a variable indicating a color of the oil and a hydrogen ion variable that is a variable indicating a hydrogen ion concentration of the oil. The execution device is configured to execute an acquisition process that is a process of acquiring the input variable and a calculation process of inputting the input variable acquired through the acquisition process to the mapping to output a value of the output variable.

Deterioration estimation device, deterioration estimation method, and non-transitory storage medium that detects a degree of deterioration of oil based on color, hydrogen ion concentration and foreign matter

An abnormality cause determining device that is applied to a vehicle including an electromagnetic actuator includes a storage device and an execution device. The storage device is configured to store map data which is data for defining a map. The map includes a current variable which is a variable indicating a current flowing actually in the electromagnetic actuator as an input variable and includes a cause variable which is a variable indicating a cause of an abnormality of an onboard unit including the electromagnetic actuator as an output variable. The execution device is configured to perform an acquisition process of acquiring a value of the input variable based on a detection value from a sensor which is mounted in the vehicle and a calculation process of calculating a value of the output variable by inputting the value of the input variable to the map.

Abnormality cause determining device, vehicular control device, and vehicular control system

An unusual-noise determination device for a vehicle that performs unusual-noise determination to determine whether a power transmission system of the vehicle is generating unusual noise. The unusual-noise determination device includes an execution device and a memory device. The memory device stores a neural network that uses the maximum sound pressure and the excess ratio as inputs, and outputs a determination result variable, which is a variable indicating a result of the unusual-noise determination. The neural network is a trained neural network that has been trained using various values related to each of multiple vehicles as training data. The execution device is configured to perform the unusual-noise determination based on an output of the trained neural network that uses, as inputs, the maximum sound pressure and the excess ratio.

Unusual-noise determination device for vehicle

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.

Vehicle control device, vehicle control system, vehicle learning device, and vehicle learning method

An oil pressure estimation device for calculating an estimated differential pressure that is an estimated value of a differential pressure between two oil chambers generated in a torque converter including the two oil chambers and a lockup clutch includes a storage device and an execution device. The storage device stores mapping data defining a mapping, the mapping outputting as an output variable an estimated differential pressure variable indicating the estimated differential pressure, in response to input of an input variable, and the mapping having been trained by machine learning. The mapping includes an instruction differential pressure variable indicating the instruction differential pressure as one of a plurality of the input variables. The execution device executes an acquisition process of acquiring a value of the input variable and a calculation process of inputting the value of the input variable into the mapping to calculate a value of the output variable.

Oil pressure estimation device and storage medium

An oil condition estimation apparatus to be applied to a vehicle in which oil is agitated by a rotator includes a storage device and an execution device. The storage device stores mapping data for defining mapping. The mapping includes, as input variables, a speed variable indicating a rotation speed of the rotator, and a pressure variable indicating a pressure of the oil, and includes, as an output variable, an air bubble variable related to air bubbles contained in the oil. The execution device executes an acquisition process for acquiring values of the input variables, and a calculation process for calculating a value of the output variable by inputting, to the mapping, the values of the input variables acquired through the acquisition process.

Oil condition estimation apparatus, vehicle control apparatus, vehicle control system, and data analysis apparatus

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.

Hydraulic pressure calculation apparatus

An apparatus to be applied to a vehicle including a transmission configured to execute a gear shifting operation for changing a gear ratio by engaging or disengaging friction engagement elements having friction members pushed by a piston that moves through hydraulic pressure supply to an oil chamber, the apparatus including: a memory storing mapping data for defining mapping, the mapping including a pressure variable and a period variable as input variables, the mapping including a stroke amount as an output variable, the pressure variable indicating a waiting pressure, the period variable indicating a waiting period; and a processor configured to: acquire values of the input variables, and calculate a value of the output variable by inputting, to the mapping, the acquired values of the input variables.

Apparatus, system, and vehicle control apparatus

There is provided a method of specifying a location of occurrence of an abnormal sound, the method including: storing mapping data in a storage device, the mapping data prescribing mapping that receives, as inputs, a sound variable that matches a sound detected in a vehicle and a state variable of a drive-system device of the vehicle synchronized with the sound, and that outputs a location as a main cause of the sound; executing a sound signal acquisition process of acquiring a sound signal output from a microphone that detects a sound; a state variable acquisition process of acquiring the state variable of the drive-system device; and a specifying process of specifying the location of occurrence of the sound corresponding to the sound signal using the sound variable and the state variable as inputs to the mapping. There are also provided a non-transitory storage medium and an in-vehicle device.

Method of specifying location of occurrence of abnormal sound, non-transitory storage medium, and in-vehicle device

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.

Heat load estimation device and heat load estimation method for friction engaging element

A driving apparatus is controlled by using a driving command that is obtained by applying an accelerator operation amount to a relation between the accelerator operation amount and the driving command for the driving apparatus, and the relation is set by using a distribution of usage of the driving command by a driver such that a gradient that is a change in the driving command with a change in the accelerator operation amount in a high usage range including a value having a longest usage time among values of the driving command is less than the gradient in a range other than the high usage range.

Control system

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.

Oil pressure learning method of automatic transmission, control device thereof, and control system thereof

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.

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Toyota, Japan

Ken Imamura