Fuzzy-logic based traction control for electric vehicles is provided. The system detects a wheel slip ratio for each wheel. The system receives an input torque command. The system determines a slip error for each wheel based on the wheel slip ratio for each wheel and a target wheel slip ratio. The system, using the fuzzy-logic based control selection technique, selects a traction control technique from one of a least-quadratic-regulator, a sliding mode controller, a loop-shaping based controller, or a model predictive controller. The system generates a compensation torque value for each wheel. The system generates the compensation torque value based on the traction control technique selected via the fuzzy-logic based control selection technique and the slip error for each wheel. The system transmits commands to actuate drive units of the vehicles based on the compensation torque value.

A method, a computer program product, and a computer system notify passengers of an imminent brake event of a vehicle. The method includes determining that the imminent brake event is about to occur. The method includes determining a delay value to be applied to a brake system of the vehicle. The method includes determining a safety threshold associated with the imminent brake event based on at least one of conditions of the vehicle and surroundings of the vehicle. As a result of the delay value being less than the safety threshold, the method includes postponing use of the brake system for a duration corresponding to the delay value. The method includes broadcasting a notification to the passengers of the imminent brake event.

A method, a computer program product, and a computer system notify passengers of an imminent brake event of a vehicle. The method includes determining that the imminent brake event is about to occur. The method includes determining a delay value to be applied to a brake system of the vehicle. The method includes determining a safety threshold associated with the imminent brake event based on at least one of conditions of the vehicle and surroundings of the vehicle. As a result of the delay value being less than the safety threshold, the method includes postponing use of the brake system for a duration corresponding to the delay value. The method includes broadcasting a notification to the passengers of the imminent brake event.

Data is received regarding vehicle braking events, each event occurring on one of a plurality of vehicles, and each event associated with a location. A determination is made that the braking events correspond to a pattern. Based on determining that the braking events correspond to the pattern, a first location is identified. In response to identifying the first location, at least one action is performed.

A vehicle includes an electric machine, friction brakes, a drivetrain, and a controller. The electric machine is configured to recharge a battery during regenerative braking. The friction brakes are configured to apply torque to wheels of the vehicle to slow the vehicle. The controller is programmed to, in response to and during an anti-locking braking event, generate a signal indicative of a total torque demand to brake the vehicle based on a difference between a desired wheel slip ratio and an actual wheel slip ratio, adjust a regenerative braking torque based on a product of the signal and a regenerative braking weighting coefficient, adjust a friction braking torque based on a product of the signal and a friction braking weighting coefficient, and further adjust the regenerative braking torque based on a closed-loop control of an estimated regenerative braking torque feedback.

A vehicle includes an electric machine, friction brakes, a drivetrain, and a controller. The electric machine is configured to recharge a battery during regenerative braking. The friction brakes are configured to apply torque to wheels of the vehicle to slow the vehicle. The controller is programmed to, in response to and during an anti-locking braking event, generate a signal indicative of a total torque demand to brake the vehicle based on a difference between a desired wheel slip ratio and an actual wheel slip ratio, adjust a regenerative braking torque based on a product of the signal and a regenerative braking weighting coefficient, adjust a friction braking torque based on a product of the signal and a friction braking weighting coefficient, and further adjust the regenerative braking torque based on a closed-loop control of an estimated regenerative braking torque feedback.

A method of training a neural network to control an aircraft system. The method includes obtaining an operational mode data space representing a set of operational modes for the aircraft system, wherein each operational mode represents a configuration of the aircraft system where performance of an aircraft component is impaired according to an aircraft system model. Each operational mode includes probability data indicating a respective probability of the operational mode occurring, according to the model. The method includes generating a reduced operational mode data space including operational modes having a probability greater than a theoretical operational probability threshold, and generating a training operational mode data space including operational modes within the reduced operational mode data space that have a probability less than a real-world operational probability threshold. The method includes training the neural network using operational modes within the training operational mode data space.

A brake system control unit includes one or more sensor interfaces configured to receive a brake torque signal from a brake torque sensor. The brake system control unit also includes a torque estimator configured to generate an estimated brake torque signal based, at least in part, on a brake model and a brake actuator command. The brake system control unit further includes control circuitry configured to generate the brake actuator command to actuate a brake actuator of a brake system. The brake actuator command is generated based on a brake pedal command and a load alleviation command The load alleviation command is based on the brake torque or the estimated brake torque signal, depending on whether a sensor fault condition associated with the brake torque sensor is detected.

A brake system control unit includes one or more sensor interfaces configured to receive a brake torque signal from a brake torque sensor. The brake system control unit also includes a torque estimator configured to generate an estimated brake torque signal based, at least in part, on a brake model and a brake actuator command. The brake system control unit further includes control circuitry configured to generate the brake actuator command to actuate a brake actuator of a brake system. The brake actuator command is generated based on a brake pedal command and a load alleviation command The load alleviation command is based on the brake torque or the estimated brake torque signal, depending on whether a sensor fault condition associated with the brake torque sensor is detected.

A vehicle includes an electric machine and a controller. The controller is programmed to, in response to releasing an accelerator pedal during a first driving scenario that is based on a first set of navigation data, increase regenerative braking torque of the electric machine to a first value. The controller is further programmed to, in response to releasing the accelerator pedal during a second driving scenario that is based on a second set of navigation data, increase the regenerative braking torque of the electric machine to a second value that is less than the first value.