(19)
(11)EP 3 636 905 A3

(12)EUROPEAN PATENT APPLICATION

(88)Date of publication A3:
29.07.2020 Bulletin 2020/31

(43)Date of publication A2:
15.04.2020 Bulletin 2020/16

(21)Application number: 19202156.6

(22)Date of filing:  09.10.2019
(51)International Patent Classification (IPC): 
F02D 41/14(2006.01)
G06N 3/04(2006.01)
G05B 13/02(2006.01)
G06N 3/08(2006.01)
(84)Designated Contracting States:
AL AT BE BG CH CY CZ DE DK EE ES FI FR GB GR HR HU IE IS IT LI LT LU LV MC MK MT NL NO PL PT RO RS SE SI SK SM TR
Designated Extension States:
BA ME
Designated Validation States:
KH MA MD TN

(30)Priority: 09.10.2018 JP 2018191237

(71)Applicant: Toyota Jidosha Kabushiki Kaisha
Aichi-ken 471-8571 (JP)

(72)Inventor:
  • NAKAMURA, Toshihiro
    Aichi-ken, 471-8571 (JP)

(74)Representative: D Young & Co LLP 
120 Holborn
London EC1N 2DY
London EC1N 2DY (GB)

  


(54)CONTROL DEVICE OF VEHICLE DRIVE DEVICE, VEHICLE-MOUNTED ELECTRONIC CONTROL UNIT, TRAINED MODEL, MACHINE LEARNING SYSTEM, METHOD OF CONTROLLING VEHICLE DRIVE DEVICE, METHOD OF PRODUCING ELECTRONIC CONTROL UNIT, AND OUTPUT PARAMETER CALCULATION DEVICE


(57) A control device 60 of a vehicle drive device comprises a processing part 81 configured to use a trained model using a neural network to calculate an output parameter of a vehicle, and a control part 82 configured to control the vehicle drive device based on the output parameter. The neural network includes a first input layer to which input parameters of the vehicle other than a design value are input, a second input layer to which the design values are input, a first hidden layer to which outputs of the first input layer are input, a second hidden layer to which outputs of the second input layer are input, and an output layer outputting the output parameter, and is configured so that the second hidden layer becomes closer to the output layer than the first hidden layer.







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