The present disclosure relates to a method and an apparatus for controlling an electronic control suspension using a deep learning-based road surface classification model. The method for controlling an electronic control suspension in a vehicle including a camera and a GPS receiver may include collecting location information of the vehicle using the GPS receiver while driving, identifying whether there is a previously generated road surface classification model corresponding to a front obstacle when the front obstacle is detected, determining a first control value based on a first characteristic value corresponding to the road surface classification model when there is the road surface classification model as a result of the identification, controlling the electronic control suspension with the determined first control value when entering the obstacle, and collecting new sensing data through a physical sensor, and correcting the first characteristic value based on the new sensing data.

A method for operating a pneumatic system having a compressed air supply system and an air spring system includes determining at least one deflection of at least one air spring of the pneumatic system. The air spring is configured to be connected to a gallery in a selectively gas-conveying manner via a valve. The method further includes determining at least one bellows volume of a spring bellows of the at least one air spring based on the at least one determined deflection, indicating a pneumatic surrogate model for the at least one bellows volume and/or for a pressure accumulator volume of a pressure accumulator of the pneumatic system based on a mass flow balance for a balance volume, and calculating, based on the pneumatic surrogate model, at least one pressure value of the at least one bellows volume, the pressure accumulator volume, and/or the balance volume.

A weight sensing assembly for a semi-trailer truck enabling balancing of a load includes a sensing module, which is one of a plurality thereof. The sensing modules are mountable to wheels of the semi-trailer truck so that each axle has a sensing module engaged to outside wheels thereof. The sensing module obtains a pressure measurement of a tire engaged to the wheel and transmits it to an electronic device. Programming code on the electronic device enables it to utilize a pressure change, upon positioning of a load upon the semi-trailer truck, to determine a weight that is positioned upon an associated axle. The electronic device calculates adjustments to positions of a sliding fifth wheel and of sliding tandems of the semi-trailer truck to obtain positions thereof that will achieve a legal weight distribution of the load. The electronic device presents, upon a screen thereof, the adjustments to a user.

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.

Map data regarding a vertical motion parameter related to a vertical motion of a wheel of a vehicle are provided. The map data have a data structure for a specific area in which a first road and a second road cross with being separated vertically. The data structure for the specific area includes at least one of: first layer map data indicating a correspondence relationship between a horizontal position, a vertical position, and the vertical motion parameter of the first road; and second layer map data indicating a correspondence relationship between a horizontal position, a vertical position, and the vertical motion parameter of the second road.

The present invention achieves suspension control that allows for synchronization of the roll and the pitch of a vehicle. This suspension control device that controls the damping force of a suspension comprises: a target pitch angle calculation unit that calculates a target pitch angle with reference to a roll angle signal; and a target control amount computation unit that calculates the roll posture target control amount referred to for controlling the damping force of the suspension by referring to a steering torque signal and the target pitch angle.

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 vehicle may include a sensor configured to acquire detecting data including front road surface information; a suspension including a spring and a damper; and a controller including a processor and a memory; wherein the controller is configured to identify an unevenness of the front road surface based on the detecting data and control the suspension based on damping force setting information corresponding to the unevenness when the vehicle reaches the unevenness.

Motion can be induced at a vehicle, e.g., by actuating components of an active suspension system, and first sensor data and second sensor data representing an environment of the vehicle can be captured at a first position and a second position, respectively, resulting from the induced motion. A second sensor can determine motion information associated with the first position and the second position. Calibration information about the sensor, the first sensor data, and the motion information can be used to determine an expectation of sensor data at the second position. A calibration error can be the difference between the second sensor data and the expected sensor data.

Provided are a vehicle, a vehicle motion state estimation apparatus, and a method for estimating a vehicle motion state capable of highly accurately estimating a state quantity of a bounce motion of a vehicle having a non-linear suspension characteristic. The vehicle motion state estimation apparatus in a vehicle, in which wheels and a vehicle body are coupled via a suspension, includes a bounce motion estimation unit that estimates and outputs a state quantity of a bounce motion of the vehicle based on traveling state information of the vehicle, and a correction value estimation unit that calculates a correction value to correct an output the bounce motion estimation unit. The correction value estimation unit calculates the correction value in consideration of a non-linear characteristic of the suspension.