IP Library Granted Patent US 11,230,985
Granted Patent B2
US 11,230,985 · App. 16/726,069 · Granted Jan 25, 2022

Control device of internal combustion engine, in-vehicle electronic control unit, machine learning system, control method of internal combustion engine, manufacturing method of electronic control unit, and output parameter calculation device

Inventor: Toshihiro Nakamura (Shizuoka-ken, JP)
Assignee: TOYOTA JIDOSHA KABUSHIKI KAISHA
F02D41/1405F02D41/2451F02D41/2477G06N3/08
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Quick Facts
Patent No.
US 11,230,985
App. No.
16/726,069
Granted
Jan 25, 2022
Kind
B2
Abstract

A control device of an internal combustion engine includes a parameter acquisition unit that acquires a plurality of input parameters, a calculation unit that calculates at least one output parameter using a neural network model, and a controller that controls the internal combustion engine. The neural network model includes a plurality of neural network units and an output layer. Each of the neural network units includes one input layer and at least one intermediate layer. The neural network model inputs different combinations of input parameters selected from the input parameters to each of the input layers of the neural network units such that a total number of input parameters to be input to the neural network units is larger than the number of the input parameters.

Claims (41)

1. A control device of an internal combustion engine, the control device comprising:

a parameter acquisition unit configured to acquire a plurality of input parameters;

a calculation unit configured to calculate at least one output parameter based on the input parameters acquired by the parameter acquisition unit using a neural network model; and

a controller configured to control the internal combustion engine based on the at least one output parameter calculated by the calculation unit, wherein:

the neural network model includes a plurality of neural network units and an output layer that outputs the at least one output parameter based on outputs of the neural network units;

each of the neural network units includes one input layer and at least one intermediate layer; and

the neural network model is configured to input different combinations of input parameters selected from the input parameters to each of the input layers of the neural network units such that a total number of combinations of input parameters to be input to the neural network units is larger than the number of the input parameters, wherein:

the number of the input parameters is n; and

the neural network model includes n C k neural network units to which n C k combinations of input parameters selected from the input parameters are input, where n is three or more and k is two to n−1.

2. The control device according to claim 1 , further comprising:

a learning unit configured to perform learning of the neural network model in a vehicle mounted with the internal combustion engine, wherein:

the parameter acquisition unit is configured to acquire the input parameters and the at least one output parameter; and

the learning unit is configured to perform the learning of the neural network model using a training data set including a combination of the input parameters and the at least one output parameter acquired by the parameter acquisition unit.

3. A control method of an internal combustion engine, the control method comprising:

acquiring a plurality of input parameters;

calculating at least one output parameter based on the input parameters using a neural network model; and

controlling the internal combustion engine based on the at least one output parameter, wherein:

the neural network model includes a plurality of neural network units and an output layer that outputs the at least one output parameter based on outputs of the neural network units;

each of the neural network units includes one input layer and at least one intermediate layer; and

the neural network model is configured to input different combinations of input parameters selected from the input parameters to each of the input layers of the neural network units such that a total number of input parameters to be input to the neural network units is larger than the number of the input parameters, wherein:

the number of the input parameters is n; and

the neural network model includes n C k neural network units to which n C k combinations of input parameters selected from the input parameters are input, where n is three or more and k is two to n−1.

4. An output parameter calculation device comprising:

a parameter acquisition unit configured to acquire a plurality of input parameters; and

a calculation unit configured to calculate at least one output parameter based on the input parameters acquired by the parameter acquisition unit using a neural network model, wherein:

the neural network model includes a plurality of neural network units and an output layer that outputs the at least one output parameter based on outputs of the neural network units;

each of the neural network units includes one input layer and at least one intermediate layer; and

the neural network model is configured to input different combinations of input parameters selected from the input parameters to each of the input layers of the neural network units such that a total number of input parameters to be input to the neural network units is larger than the number of the input parameters, wherein:

the number of the input parameters is n; and

the neural network model includes n C k neural network units to which n C k combinations of input parameters selected from the input parameters are input, where n is three or more and k is two to n−1.

5. The control device according to claim 1 , wherein the neural network is received from a server outside a vehicle by the vehicle.

6. The control method according to claim 3 , further comprising receiving the neural network from a server outside of a vehicle including the internal combustion engine.

7. The control method according to claim 3 , further comprising:

learning by the neural network model in a vehicle mounted with the internal combustion engine, wherein:

acquiring the plurality of input parameters further comprises acquiring the at least one output parameter; and

the learning of the neural network model comprises using a training data set including a combination of the input parameters and the at least one output parameter.

8. The output parameter calculation device according to claim 4 , wherein the neural network is received from a server outside a vehicle by the vehicle.

9. The output parameter calculation device according to claim 4 , further comprising:

a learning unit configured to perform learning of the neural network model in a vehicle mounted with the internal combustion engine, wherein:

the parameter acquisition unit is configured to acquire the input parameters and the at least one output parameter; and

the learning unit is configured to perform the learning of the neural network model using a training data set including a combination of the input parameters and the at least one output parameter acquired by the parameter acquisition unit.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Dec 23, 2019
From: NAKAMURA, TOSHIHIRO
To: TOYOTA JIDOSHA KABUSHIKI KAISHA
Reel/Frame 051415/0306 →
Priority Claims (1)
JP JP2019-017146 · Feb 1, 2019 · national
Continuity (1)
Related Publication 20200248641A1 · Aug 6, 2020