# US 11,440,559 B2 · Machine learning device and machine learning system

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- Number: US 11,440,559 B2
- Document ID: US11440559B2
- Status: Granted
- Kind: B2
- Application number: 17/405,390
- Filed: 2021-08-18
- Published: 2022-02-24
- Granted: 2022-09-13
- Earliest claimed: 2020-08-20
- Assignees: Toyota Jidosha Kabushiki Kaisha
- Applicants: Toyota Jidosha Kabushiki Kaisha
- Inventors: Daiki Yokoyama; Yohei Hareyama
- Web page: https://patentgrep.com/patent/US11440559B2

## CPC

- B60W 50/0097: {Predicting future conditions}
- B60W 50/06: Improving the dynamic response of the control system, e.g. improving the speed of regulation or avoiding hunting or overshoot
- G06N 3/063: using electronic means
- B60W 2050/0002: {Automatic control, details of type of controller or control system architecture}
- B60W 2050/0075: {Automatic parameter input, automatic initialising or calibrating means}
- B60W: CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- G06N: COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS

## Abstract

The machine learning device includes a predicting part configured to use a machine learning model to predict predetermined information, an updating part configured to update the machine learning model, and a part information acquiring part configured to detect replacement of a vehicle part and acquire identification information of the vehicle part after replacement. The updating part is configured to receive a new machine learning model trained using training data sets corresponding to the vehicle part after replacement from a server and apply the new machine learning model to the vehicle, if a vehicle part relating to input data of the machine learning model is replaced with a vehicle part of a different configuration.

## Claims

### Claim 1

A machine learning device provided in a vehicle, comprising a processor configured to:
control actuators of the vehicle;
predict predetermined information with a machine learning model;
update the machine learning model;
detect an electronic signal indicative of a replacement of a first vehicle part;
acquire identification information of a second vehicle part which is installed instead of the first vehicle part after the replacement; and
receive a new machine learning model trained using training data sets corresponding to the second vehicle part after the replacement from a server and apply the new machine learning model to the vehicle, in response to the first vehicle part relating to input data of the machine learning model having a different configuration than the second vehicle part.

### Claim 2 (depends on 1)

The machine learning device according to claim 1, wherein the processor is configured to transmit the identification information of the second vehicle part after replacement and identification information of the vehicle to the server, and the new machine learning model is a machine learning model corresponding to the identification information of the vehicle.

### Claim 3 (depends on 1)

The machine learning device according to claim 1, wherein the machine learning model is a neural network model.