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US 12,311,949 B2Granted
Vehicle control system
AssigneeFaiveley Transport Italia S.P.A.
InventorRoberto Tione
Life of this patent
Estimating the term…
Abstract
A vehicle control system may be provided for controlling adhesion of wheels to a route surface. The control system includes one or more processors configured to determine adhesion values representative of adhesion between the wheels of a vehicle and the route surface based on angular speeds of the wheels. An artificial intelligence neural network may generate a target slip value for the wheels that are coupled with at least two different axles of the vehicle by processing the adhesion values and modifying the target slip value to increase an average value of the adhesion values of the wheels. The one or more processors may control a torque applied to at least one of the axles based on the target slip value.
Claims20
A vehicle control system comprising:
- one or more processors configured to determine adhesion values representative of adhesion between wheels of a vehicle and a route surface based on angular speeds of the wheels,
- an artificial intelligence (AI) neural network having artificial neurons arranged in layers and connected with each other by connections, the AI neural network configured to subsequently calculate a target slip value for the wheels that are coupled with at least two different axles of the vehicle using the adhesion values that were determined, the AI neural network also configured to repeatedly modify the target slip value to increase an average value of the adhesion values of the wheels,
- the one or more processors configured to control a torque applied to at least one of the axles based on the target slip value that is calculated,
- the AI neural network configured to receive feedback regarding the target slip value that is calculated and modified by the artificial neurons,
- the AI neural network configured to be trained by changing one or more connections between the artificial neurons in the AI neural network based on the feedback that is received.
2 more elements
A method comprising:
- Determining, using one or more processors, adhesion values representative of adhesion between wheels of a vehicle and a mute surface based on angular speeds of the wheels;
- calculating a target slip value for the wheels that are coupled with at least two different axles of the vehicle, the target slip value calculated using the adhesion values that were determined;
- calculating the target slip value using an artificial intelligence (AI) neural network having artificial neurons arranged in layers and connected with each other by connections;
- controlling, using the one or more processors, a torque applied to at least one of the axles based on the target slip value;
- repeatedly changing the target slip value as the vehicle moves based on changes in the adhesion values to increase an average value of the adhesion values, changing the target slip values using the AI neural network;
- receiving feedback regarding the target slip value that is calculated and changed by the artificial neurons;
- and
- training the AI neural network by changing one or more connections between the artificial neurons in the AI neural network based on the feedback that is received.
5 more elements
A system comprising:
- one or more processors configured to determine adhesion values representative of adhesion between wheels of a vehicle and a mute surface based on angular speeds of the wheels,
- an artificial intelligence (AI) neural network having artificial neurons arranged in layers and connected with each other by connections configured to calculate a target slip value for the wheels that are coupled with at least two different axles of the vehicle using the adhesion values that were determined,
- are the AI neural network configured to repeatedly change the target slip value as the vehicle moves based on changes in the adhesion values to increase an average value of the adhesion value,
- the artificial neurons configured to receive feedback regarding the target slip value that is calculated,
- the AI neural network configured to be trained by changing one or more connections between the artificial neurons in the AI neural network based on the feedback that is received,
- the one or more processors configured to control a torque applied to at least one of the axles based on the target slip value,
- wherein the wheels include a leading wheel and a trailing wheel along a direction of movement of the vehicle, the AI neural network configured to increase the target slip value that is calculated associated with the leading wheel to clean the route surface with the leading wheel prior to travel of the trailing wheel.
4 more elements
Dependencies are inferred from the claim text.