A control method for hybrid electromagnetic suspension. The method provides four modes for hybrid electromagnetic suspension: a comfort mode, a sport mode, a combined mode, and an energy feedback mode. A driver can switch between the four modes as desired. For the comfort, sport, and combined modes, hybrid control is adopted, and two sub-modes are provided: an active control mode and a semi-active control mode. A switching condition between the two sub-modes is determined by using a novel parameter C.sub.act and comparing the same against a maximum equivalent electromagnetic damping coefficient C.sub.eqmax of a linear motor. The present invention solves the problem of achieving a balance between suspension comfort and tire traction, and meets the demands of different operating conditions and users by enabling manual mode switching. In addition, the hybrid control is employed to solve the problems of high energy consumption of active suspension and limited control performance of semi-active suspension, thus ensuring good kinematic performance of automobile suspension while reducing energy consumption. Furthermore, the energy feedback mode is designed to enable the suspension to perform energy recovery, meeting demands of energy conservation and emission reduction.

A vehicle includes a suspension system having a first damper, a second damper, valves and a controller. Each of the first damper and the second damper include a housing and a piston sealingly interfaced with an inner diameter of the housing, dividing the damper into a first and second chamber. Each valve controls flow rate of fluid entering or exiting at least one of the first and second chamber of at least one of the first damper and the second damper. The controller controls the valves to control extension or compression of at least one of the first damper and the second damper based on at least one of a degree of roll of the vehicle during a turn of the vehicle and a degree of pitch of the vehicle during acceleration of the vehicle or a degree of pitch of the vehicle during deceleration of the vehicle.

Disclosed is an automatic vehicle suspension tuning system. The system has a control module to receive user input, an ECU with a processor and a memory, one or more road condition sensors, and one or more controllable suspension system components. The ECU controls the adjustments of the controllable suspension system component in response to user input to the control module as well as input from the road condition sensors during operation of the vehicle. A method of tuning a controllable suspension system component is also disclosed.

The invention relates to a wheel suspension control system for a vehicle. The system comprises a suspension device, a wheel end bearing, at least one vibration sensor and a processing circuitry. The vibration sensor is provided at or in the wheel end bearing for measuring vibrations propagated from the road wheel to the wheel end bearing when the road wheel travels on a road having surface variations, wherein the vibration sensor is configured to transmit measurement signals representing the measured vibrations. The processing circuitry is configured to receive the transmitted measurement signals and to control at least one suspension parameter of the suspension device based on the received measurement signals. The invention also relates to a vehicle and to a method for controlling a suspension device.

The present invention provides a control device of a vehicle, comprising: a detector configured to detect acceleration in a front-and-rear direction generated in the vehicle; and an estimation unit configured to calculate a braking force of the entire vehicle and a pitch angle of the vehicle based on the acceleration detected by the detector, and estimate an amount of nose dive of the vehicle during braking of the vehicle based on the calculated braking force of the entire vehicle and the calculated pitch angle of the vehicle.

A behavior control device for a vehicle includes: a first actuator configured to apply a vertical control force to a left wheel on a first axle, the first axle being a front axle or a rear axle of the vehicle; a second actuator configured to operate independently of the first actuator and to apply a vertical control force to a right wheel on the first axle; and a controller. The controller is configured to calculate a required value of a behavior parameter representing a behavior of the vehicle, convert the required value of the behavior parameter to a first required force for the first actuator and a second required force for the second actuator, and control the first actuator such that the vertical control force applied to the left wheel on the first axle becomes the first required force.

A damping control system for a vehicle having a suspension located between a plurality of ground engaging members and a vehicle frame includes at least one adjustable shock absorber having an adjustable damping profile and a driver actuatable input. The driver actuatable input may be positioned to be actuatable by the driver in the absence of requiring a removal of either of the hands of the driver from a steering device of the vehicle.

A damping control system for a vehicle having a suspension located between a plurality of ground engaging members and a vehicle frame includes at least one adjustable shock absorber having an adjustable damping profile and a driver actuatable input. The driver actuatable input may be positioned to be actuatable by the driver in the absence of requiring a removal of either of the hands of the driver from a steering device of the vehicle.

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 computer-implemented method for damping a vehicle, including: receiving external load data for the vehicle; receiving at least one damper velocity of a damper of the vehicle; providing an optimization model configured to describe a relation between external load data for a vehicle, at least one damper velocity of a damper of a vehicle, and at least one damper force of the at least one damper; determining at least one damper force of the damper for the vehicle by inputting the external load data and the at least one damper velocity into the optimization model; and providing the at least one damper force of the at least one damper of the vehicle.