US 12,509,037 B2Granted

Vehicle braking assembly

AssigneeFaiveley Transport Italia S.P.A.

InventorsRoberto Tione, Andrea Cavazzin, Angelo Grasso

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Abstract

A system including a supply valve disposed between a chamber and a pressure source, a discharge valve disposed between the chamber and an external atmosphere, a first control unit, and a second control unit. The first control unit coupled with the supply valve by a first switch and with the discharge valve by a second switch. The first control unit outputting signals to the first and second switches to control the supply and discharge valves. The second control unit coupled with the discharge valve by a third switch and a fourth switch, the second control unit outputting signals to the third and fourth switches to control the supply and discharge valves. The first control unit may include a first microcontroller to control the signals of the first control unit using an artificial intelligence (AI) neural network having artificial neurons arranged in layers and connected with each other by connections.

Claims20

Dependent claims

An assembly comprising:

a supply valve configured to be disposed between a chamber and a pressure source;
a discharge valve disposed between the chamber and an external atmosphere;
first and second control units that control a pressure in the chamber;
the first control unit being coupled with the supply valve by a first switch and with the discharge valve by a second switch, the first control unit configured to output signals to the first switch and the second switch to control the supply valve and the discharge valve;
and
the second control unit being coupled with the discharge valve by a third switch and with the supply valve by a fourth switch, the second control unit configured to output signals to the third switch and the fourth switch to control the supply valve and the discharge valve,
wherein the first control unit includes a first microcontroller configured to control determine the signals output by the first control unit, via using an artificial intelligence (AI) neural network,
the AI neural network having artificial neurons arranged in layers and connected with each other by connections,
the layers including an input layer, one or more intermediate layers and an output layer,
the input layer comprising input neurons configured to receive inputs to the AI neural network, the inputs including a signal representing the pressure in the chamber,
wherein, based on the inputs, one or more neurons in the one or more intermediate layers and/or the output layer are configured to determine a preferred operation and generate an output that relates to the preferred operation and that translates to the signals output by the first control unit,
the first microcontroller configured to:
receive feedback based on the signals that are output by the first control unit,
based on the received feedback, provide additional inputs to the AI neural network, and
thereby train the AI neural network by changing one or more of the connections between the artificial neurons in the AI neural network.

12 more elements

An assembly comprising:

first and second control units that control a pressure in a chamber;
the first control unit being coupled with a supply valve by a first switch and with a discharge valve by a second switch, the first control unit configured to output signals to the first switch and the second switch to control the supply valve and the discharge valve;
and
the second control unit being coupled with the discharge valve by a third switch and with the supply valve by a fourth switch, the second control unit configured to output signals to the third switch and the fourth switch to control the supply valve and the discharge valve,
wherein the first control unit includes a first microcontroller configured to control determine the signals output by the first control unit, via using an artificial intelligence (AI) neural network,
the AI neural network having artificial neurons arranged in layers and connected with each other by connections,
the layers including an input layer, one or more intermediate layers and an output layer,
the input layer comprising input neurons configured to receive inputs to the AI neural network, the inputs including a signal representing the pressure in the chamber,
wherein, based on the inputs, one or more neurons in the one or more intermediate layers and/or the output layer are configured to determine a preferred operation and generate an output that relates to the preferred operation and that translates to the signals output by the first control unit,
the first microcontroller configured to:
receive feedback based on the signals that are output by the first control unit,
based on the received feedback, provide additional inputs to the AI neural network, and
thereby train the AI neural network by changing one or more of the connections
between the artificial neurons in the AI neural network,
wherein the first control unit and the second control unit are configured to output the signals such that the supply valve and the discharge valve open or close based on whether the signals from the first control unit match or conflict with the signals from the second control unit.

12 more elements

An assembly comprising:

a supply valve and a discharge valve coupled in series with each other between a pressure source and an external atmosphere, the supply valve and the discharge valve configured to be coupled with a chamber that is pressurized by the pressure source;
first and second control units that control a pressure in the chamber;
the first control unit being coupled with the supply valve by a first switch and with the discharge valve by a second switch, the first control unit configured to output signals to the first switch and the second switch to control the supply valve and the discharge valve;
and
the second control unit being coupled with the discharge valve by a third switch and with the supply valve by a fourth switch, the second control unit configured to output signals to the third switch and the fourth switch to control the supply valve and the discharge valve,
wherein the first control unit includes a first microcontroller configured to control determine the signals output by the first control unit, via using an artificial intelligence (AI) neural network,
the AI neural network having artificial neurons arranged in layers and connected with each other by connections,
the layers including an input layer, one or more intermediate layers and an output layer,
the input layer comprising input neurons configured to receive inputs to the AI neural network, the inputs including a signal representing the pressure in the chamber,
wherein, based on the inputs, one or more neurons in the one or more intermediate layers and/or the output layer are configured to determine a preferred operation and generate an output that relates to the preferred operation and that translates to the signals output by the first control unit,
the first microcontroller configured to:
receive feedback based on the signals that are output by the first control unit,
based on the received feedback, provide additional inputs to the AI neural network, and
thereby train the AI neural network by changing one or more of the connections between the artificial neurons in the AI neural network.

11 more elements

Dependencies are inferred from the claim text.

Facts

Application: 17/962,988Filed 10 Oct 2022 · continuation in part
Priority: IT TO2014A00094513 Nov 2014
Published: US 2023/0042019 A19 Feb 2023
Granted: 30 Dec 2025
Term ends: Not estimatedThe source records don’t support an estimate.

Classification18 codes

B60T 7/122
For automatic initiation; for initiation not subject to will of driver or passenger: for locking of reverse movement
B60T 8/174
Using electrical or electronic regulation means to control braking: characterised by using special control logic, e.g. fuzzy logic , neural computing
B60T 8/1893
Responsive to vehicle weight or load, e.g. load distribution: especially adapted for railway vehicles
B60T 8/366
Continuously controlled electromagnetic valves: valve details

Family

PCT/IB2015/058730Parent of this continuation-in-part · filed 12 Nov 2015
Application16/725,326Parent of this continuation-in-part · filed 23 Dec 2019
US 10,538,229 B2Parent of this continuation-in-part · filed 21 Jan 2020
US 2023/0042019 A1Pre-grant publication · published 9 Feb 2023
US 11,498,541 B2Parent of this continuation-in-part
Application15/524,053Parent of this continuation-in-part
US 2018/0297570 A1Published application
US 2020/0130668 A1Published application
US 12,509,037 B2This patent

From the US filing history. Foreign family members aren’t listed.