In some examples, a vehicle suspension for supporting, at least in part, a sprung mass, includes a damper connected to the sprung mass, the damper including a movable piston. The vehicle suspension further includes an actuator and a controller. The controller may be configured to determine a frequency of motion associated with the sprung mass. When the frequency of motion is below a first frequency threshold, the controller may send a control signal to cause the actuator to apply a deceleration force to the sprung mass. Further, when the frequency of motion associated with the sprung mass exceeds the first frequency threshold, the controller may send a control signal to cause the actuator to apply a compensatory force to the sprung mass. For instance, a magnitude of the compensatory force may be based on a friction force determined for the damper.

An electromechanical chassis actuator, for example an actuator of a roll stabilizer, for a motor vehicle has a torque measuring arrangement based on the inverse magnetostrictive principle. At least one electronic unit has a printed circuit board which is connected at least indirectly to an actuator housing through a rivet connection.

An electric suspension apparatus includes electric actuators provided for a plurality of wheels, respectively, an acceleration sensor disposed in each of the electric actuators, the acceleration sensor detecting a first acceleration, and an electric suspension control ECU controlling each of the electric actuators based on the first acceleration, and the electric suspension control ECU decreases a control amount to the electric actuator, in a case where a first speed based on the first acceleration in an up-down direction is equal to or less than a predetermined speed.

Example illustrations are directed to a damping system for a vehicle suspension that includes a controller configured to determine a roughness of a ground surface associated with the vehicle. The controller is also configured to determine a damper setting for the damping system based on the determined roughness. A method is also provided that includes determining, using a controller, a roughness of a ground surface associated with the vehicle. The method may further include determining, using the controller, a damper setting of the vehicle based on the determined roughness.

Disclosed herein are system, method, and computer program product embodiments for detecting potentially unsafe wear levels in vehicle suspension systems. An embodiment operates by receiving acoustic signals of a vehicle suspension system, processing, the acoustic signals to generate training data, training a predictive learning algorithm to generate a predictive wear model and classifying the processed acoustic signals to indicate wear levels of one or more components of the vehicle suspension system. The trained predictive wear model subsequently predicts wear levels of the vehicle suspension system for notification to a cloud-based repository. Fleets of driverless vehicles may continuously monitor wear levels for timely maintenance before failure occurs.

A vehicle position estimation method includes: acquiring time-series data of a parameter related to a vertical motion of a wheel while the vehicle is traveling; acquiring the parameter around the vehicle, as a reference parameter, from a parameter map indicating a correspondence relationship between the parameter and a position; estimating a vehicle position based on a comparison between the time-series data of the parameter and time-series data of the reference parameter. Meanwhile, road surface roughness around the vehicle in a lateral direction and a lateral position of the vehicle in a road are recognized by using a recognition sensor installed on the vehicle. When the road surface roughness is less than a threshold, a lateral position component of the estimated vehicle position is replaced with the lateral position recognized by using the recognition sensor.

A vehicle control device includes a vertical VSE, a riding comfort control logic, a planar VSE, a steering stability control logic, a command limiting unit, a control command selection unit. The command limiting unit acquires specifications related to a traveling of a vehicle such as, for example, a slip rate and a four-wheel independent braking/driving force control flag through a CAN. The command limiting unit limits a variable range of a damping force generated by a suspension device provided between a vehicle body and wheels of the vehicle based on the specifications related to the traveling of the vehicle to obtain a first command value. The command limiting unit outputs the obtained first command value to the control command selection unit.

A system for filling a tank of a suspension system with hydraulic fluid includes: a module configured to turn on an external pump and pump hydraulic fluid into the suspension system, where the external pump is separate from the suspension system and is configured to pump hydraulic fluid into the suspension system via a port fluidly connected to a hydraulic line of the suspension system; and a fill module configured to, after operating the external pump, operate a pump of the suspension system and pump hydraulic fluid from the hydraulic line into the tank of the suspension system thereby filling the tank.

An electrically powered suspension system includes: an electromagnetic actuator that is provided between a vehicle body and a wheel of a vehicle and generates a load for damping vibration of the vehicle body; an information acquisition part that acquires information on a state of a road surface ahead of the vehicle; a target load calculation part that calculates a target load for preview control based on the road surface state, and a load control part that performs load control on the electromagnetic actuator. The target load calculation part estimates an actual input timing based on the vehicle speed and calculates an adjustment start timing related to suspension characteristics, based on the estimated actual input timing. When estimating the actual input timing based on the vehicle speed, the target load calculation part applies, to the vehicle speed, a correction coefficient for correcting a fluctuation of the vehicle speed.

A sensory evaluation prediction system includes an input unit that reads an output from a behavior sensor that measures two or more types of pieces of time series information regarding a moving body, a selection unit that selects two or more types of physical quantities from the output from the behavior sensor read by the input unit, a correlation creation unit that creates information showing a correlation in time series between the two or more types of the physical quantities selected by the selection unit, and an evaluation circuit that calculates an evaluation value of a sensory index based on the information showing the correlation in time series.