Abstract: The disclosure relates to a method including the steps of: acquiring a time sequence of sets of vehicle parameter values; determining, for each set of acquired vehicle parameter values, based the set of acquired vehicle parameter values, a measure indicative of an observed strain in a steering rod, between a steering actuator and a wheel; determining, for each set of acquired vehicle parameter values, a measure indicative of a predicted strain in the rod, between the steering actuator and the wheel; and determining the functional status of the steering system based on a relation between the measures indicative of the observed strain in the rod and the measures indicative of the predicted strain in the rod.

Abstract: Machine-learning-based steering torque non-uniformity compensation for vehicles is enabled. For example, a system can comprise a memory that stores computer executable components, and a processor that executes the computer executable components stored in the memory, wherein the computer executable components comprise: a machine learning component that generates a steering non-uniformity model based on machine learning applied to past steering data representative of positions and steering ratios of a steering wheel of a vehicle, and a torque compensation component that, using current position data representative of a current position of the steering wheel and the steering non-uniformity model, determines a torque to apply to the steering wheel configured to offset a steering non-uniformity at the current position.

Abstract: A method and system for compensating for vehicle disturbances during vehicle operation, including: an algorithm for obtaining predicted driving condition data from a database, wherein the database includes one or more of geospatial data and remote vehicle data; an algorithm for obtaining real-time vehicle state data from equipment communicatively connected to a vehicle; an algorithm for combining the predicted driving condition data and the real-time vehicle state data to formulate a desired steering torque request necessary to compensate for predicted and actual driving conditions experienced by the vehicle; and an algorithm for providing the desired steering torque request to a power steering assist system of the vehicle to compensate for the predicted and actual driving conditions experienced by the vehicle.

Abstract: Machine-learning-based steering torque non-uniformity compensation for vehicles is enabled. For example, a system can comprise a memory that stores computer executable components, and a processor that executes the computer executable components stored in the memory, wherein the computer executable components comprise: a machine learning component that generates a steering non-uniformity model based on machine learning applied to past steering data representative of positions and steering ratios of a steering wheel of a vehicle, and a torque compensation component that, using current position data representative of a current position of the steering wheel and the steering non-uniformity model, determines a torque to apply to the steering wheel configured to offset a steering non-uniformity at the current position.

Abstract: A method and system for compensating for vehicle disturbances during vehicle operation, including: an algorithm for obtaining predicted driving condition data from a database, wherein the database includes one or more of geospatial data and remote vehicle data; an algorithm for obtaining real-time vehicle state data from equipment communicatively connected to a vehicle; an algorithm for combining the predicted driving condition data and the real-time vehicle state data to formulate a desired steering torque request necessary to compensate for predicted and actual driving conditions experienced by the vehicle; and an algorithm for providing the desired steering torque request to a power steering assist system of the vehicle to compensate for the predicted and actual driving conditions experienced by the vehicle.

Abstract: The disclosure relates to a method including the steps of: acquiring a time sequence of sets of vehicle parameter values; determining, for each set of acquired vehicle parameter values, based the set of acquired vehicle parameter values, a measure indicative of an observed strain in a steering rod, between a steering actuator and a wheel; determining, for each set of acquired vehicle parameter values, a measure indicative of a predicted strain in the rod, between the steering actuator and the wheel; and determining the functional status of the steering system based on a relation between the measures indicative of the observed strain in the rod and the measures indicative of the predicted strain in the rod.