A system for determining a displacement velocity signal for controlling an active wheel suspension of a land vehicle by open-loop and/or closed-loop control includes at least one Kalman filter, and at least one acceleration sensor arranged on a sprung mass of the land vehicle to sense a vertical acceleration of the sprung mass and to generate a corresponding acceleration signal supplied to the Kalman filter. The Kalman filter includes a mathematical motion model of the sprung mass, and input states of the Kalman filter include a vertical acceleration of the sprung mass, a vertical displacement velocity of the sprung mass, and a vertical displacement distance of the sprung mass. A displacement measurement signal having a value 0 is supplied continuously to the Kalman filter to determine the displacement velocity signal. Constant noise variance values of a measurement noise covariance matrix of the Kalman filter that are assigned to the displacement measurement signal are, in each case, set at one half of a maximum vertical displacement distance of the sprung mass.

A self-calibrating scanning system and method provides a novel way to eliminate errors in scanning systems, such as lidar or radar detection, using an inertial measurement unit. The system includes an energy transmission source configured to transmit an energy signal through a transmittal area. A detector receives a return energy signal of at least one target object of the energy transmitter source within the transmittal area. The system calculates at least one of the range and position of an object from information relating to at least one of the time and phase of the return energy signal relative to the transmittal energy signal. The spatial or angular displacement of the detector relative to the light source is measured using data from the inertial measurement unit, and at least one of calculated range and position of the object is adjusted based on the spatial or angular displacement of the detector.

Disclosed is a load detection device and method using the same. In one example, the device includes a height-level measuring unit configured to determine a height level of a vehicle and to generate at least one height-level signal that characterizes the height level. A position-measuring unit is configured to determine the position of the vehicle relative to the mid-point of the earth and to generate at least one position signal that characterizes the vehicle position. An evaluation unit is coupled to the height-level measuring unit and to the position-measuring unit. The evaluation unit is configured to determine a mass of a load of the vehicle, taking into account the height-level signal(s) and the position signal(s). The device can be used to determine the mass of the load, which may include a number of persons.

An object is to provide a signal processing device capable of reducing a sudden change in the rate of change of an output signal at the time of switching between two signals. In the signal processing device, when a signal of a larger value is selected, a smoothing signal is generated based on the deviation between two signals such that the smoothing signal has a value larger than the values of the two signals between two points at which the smoothing signal intersects the two signals, or when a signal of a smaller value is selected, the smoothing signal is generated based on the deviation between two signals such that the smoothing signal has a value smaller than the values of the two signals between two points at which the smoothing signal intersects the two signals.

A road surface friction coefficient estimation apparatus for a vehicle includes: a first estimator; a second estimator; and a third estimator. The first estimator estimates a first road surface friction coefficient on a basis of a vehicle information acquired from the vehicle. The second estimator estimates a second road surface friction coefficient on a basis of an external information acquired from an outside of the vehicle. The third estimator estimates a road surface friction coefficient from the first road surface friction coefficient and the second road surface friction coefficient on a basis of a first reliability degree and a second reliability degree, the first reliability degree indicating a reliability of the first road surface friction coefficient, the second reliability degree indicating a reliability of the second road surface friction coefficient.

A method of calculation a vehicle load comprising a first vehicle load value based at least on air pressures in air springs and height data of suspension of a vehicle axle, determining a second vehicle load value based on a change of track width of the vehicle axle, and calculating the vehicle load based on the first vehicle load value and the second vehicle load value.

A strain sensor system having a first base plate with an elongate shape defining a first longitudinal axis, a first strain sensor disposed on the first base plate, a second base plate having an elongate shape defining a second longitudinal axis, a second strain sensor disposed on the second base plate, and a control unit configured to process measurement data produced by the first strain sensor and by the second strain sensor, wherein the first base plate and the second base plate are disposed such that the first longitudinal axis is arranged orthogonally or essentially orthogonally with respect to the second longitudinal axis.

A strain sensor system having a first base plate with an elongate shape defining a first longitudinal axis, a first strain sensor disposed on the first base plate, a second base plate having an elongate shape defining a second longitudinal axis, a second strain sensor disposed on the second base plate, and a control unit configured to process measurement data produced by the first strain sensor and by the second strain sensor, wherein the first base plate and the second base plate are disposed such that the first longitudinal axis is arranged orthogonally or essentially orthogonally with respect to the second longitudinal axis.

An object of the present invention is to provide a vehicle motion state estimation device and method that can estimate the vertical motion state amount with high accuracy by taking into consideration vertical force in which the frictional force acting in the front-rear direction or lateral direction of the wheel acts on the vehicle body due to the geometry of suspension. A vehicle motion state estimation device in a vehicle in which a wheel and a vehicle body are coupled via a suspension, the vehicle motion state estimation device including: a vertical motion-caused wheel speed component estimation unit that estimates a wheel speed component caused by vertical motion of the vehicle; a vertical force estimation unit that calculates vertical force in which frictional force of the wheel caused by motion of the vehicle acts on the vehicle body by geometry of the suspension; and a vertical motion estimation unit that estimates a state amount of vertical motion of a vehicle, in which the vertical motion estimation unit estimates a state amount of vertical motion of the vehicle based on a wheel speed component from the vertical motion-caused wheel speed component estimation unit and vertical force acting on the vehicle body from the vertical force estimation unit.

An object of the present invention is to provide a vehicle motion state estimation device and method that can estimate the vertical motion state amount with high accuracy by taking into consideration vertical force in which the frictional force acting in the front-rear direction or lateral direction of the wheel acts on the vehicle body due to the geometry of suspension. A vehicle motion state estimation device in a vehicle in which a wheel and a vehicle body are coupled via a suspension, the vehicle motion state estimation device including: a vertical motion-caused wheel speed component estimation unit that estimates a wheel speed component caused by vertical motion of the vehicle; a vertical force estimation unit that calculates vertical force in which frictional force of the wheel caused by motion of the vehicle acts on the vehicle body by geometry of the suspension; and a vertical motion estimation unit that estimates a state amount of vertical motion of a vehicle, in which the vertical motion estimation unit estimates a state amount of vertical motion of the vehicle based on a wheel speed component from the vertical motion-caused wheel speed component estimation unit and vertical force acting on the vehicle body from the vertical force estimation unit.