Aspects of self-powered weigh-in-motion systems and methods that utilize piezoelectric components for sensing load as well as powering data acquisition and analysis components. In one example, the weigh-in-motion system includes a number of piezoelectric stacks, each stack including a number of piezoelectric elements. Each stack includes one or more top or upper piezoelectric element that provides vehicle sensing data. Each stack also includes a set of piezoelectric elements used for energy harvesting. The sensing piezoelectric elements are connected to a data input of a microcontroller for vehicle classification, while the energy harvesting piezoelectric elements are connected to a power input of the microcontroller.

A charging system includes load meters mounted in a vehicle, the load meters each measuring a load exerted on an axle or a wheel and deciding a measurement result and an onboard unit that acquires the measurement results of the load meters and is capable of communicating weight information on the weight of the vehicle based on the measurement results to a roadside machine.

Vehicle center of gravity (CoG) height and mass estimation techniques utilize a light detection and ranging (LIDAR) sensor configured to emit light pulses and capture reflected light pulses that collectively form LIDAR point cloud data and a controller configured to estimate the CoG height and the mass of the vehicle during a steady-state operating condition of the vehicle by processing the LIDAR point cloud data to identify a ground plane, identifying a height difference between (i) a nominal distance from the LIDAR sensor to the ground plane and (ii) an estimated distance from the LIDAR sensor to the ground plane using the processed LIDAR point cloud data, estimating the vehicle CoG height as a difference between (i) a nominal vehicle CoG height and the height difference, and estimating the vehicle mass based on one of (i) vehicle CoG metrics and (ii) dampening metrics of a suspension of the vehicle.

Vehicle center of gravity (CoG) height and mass estimation techniques utilize a light detection and ranging (LIDAR) sensor configured to emit light pulses and capture reflected light pulses that collectively form LIDAR point cloud data and a controller configured to estimate the CoG height and the mass of the vehicle during a steady-state operating condition of the vehicle by processing the LIDAR point cloud data to identify a ground plane, identifying a height difference between (i) a nominal distance from the LIDAR sensor to the ground plane and (ii) an estimated distance from the LIDAR sensor to the ground plane using the processed LIDAR point cloud data, estimating the vehicle CoG height as a difference between (i) a nominal vehicle CoG height and the height difference, and estimating the vehicle mass based on one of (i) vehicle CoG metrics and (ii) dampening metrics of a suspension of the vehicle.

The present invention proposes a method for identifying the spatial-temporal distribution of the vehicle loads on a bridge based on the DenseNet. The method includes five steps: firstly, mounting a plurality of cameras in different positions of a bridge, acquiring images of the bridge from different directions, and outputting video images with time tags; secondly, acquiring multichannel characteristics of vehicles on the bridge by using DenseNet, including color characteristics, shape characteristics and position characteristics; thirdly, analyzing the data and characteristics of the vehicles from different cameras at a same moment to obtain vehicle distribution on the bridge at any time; fourthly, continuously monitoring the vehicle distribution in a time period to obtain a vehicle load situation on any section of the bridge; and finally, integrating the time and space distribution of the vehicles to obtain spatial-temporal distribution of the bridge.

A load meter includes a detector, a storage unit, and a load calculator. The detector detects, by using a captured image obtained by capturing a road and a vehicle present on the road, a displacement amount in the captured image, the displacement amount corresponding to displacement caused on the road by application of a load of the vehicle. The storage unit stores information indicating a relation between the load and the displacement amount. The load calculator calculates the load based on the displacement amount and the information.

A load meter includes a detector, a storage unit, and a load calculator. The detector detects, by using a captured image obtained by capturing a road and a vehicle present on the road, a displacement amount in the captured image, the displacement amount corresponding to displacement caused on the road by application of a load of the vehicle. The storage unit stores information indicating a relation between the load and the displacement amount. The load calculator calculates the load based on the displacement amount and the information.

The present invention relates to a vehicle (10) comprising an arrangement for determining the weight of load on the vehicle, said vehicle (10) comprising: a vehicle body (11, 12); at least two ground support assemblies (30; 130; 230) arranged to support said vehicle body (11, 12), each ground support assembly comprises a support beam (31; 131; 231) arranged to support at least two wheels (132; 232), or track road wheels (32), at least one sprocket (33) and an endless track (34) arranged around the track road wheels (32) and the sprocket (33); a suspension device (40; 140; 240) for suspension of each of said ground support assemblies (30; 130; 230) to said vehicle body (11, 12), said suspension device (40; 140; 240) is arranged to allow a movement of the ground support assembly (30; 130; 230) relative to the vehicle body (11, 12) in a substantially vertical plane extending in the longitudinal direction of said ground support assembly (30; 130; 230); and a control unit (70), wherein said suspension device (40; 140; 240) comprises sensors arranged to measure the loads on the respective ground support assembly (30; 130; 230) and forward the information to the control unit (70) where the weight of the vehicle load is determined based on the information from the sensors.

The invention relates to a method for calculating the weight of a load moving on scales (1). According to the method, a load signal of the scales is determined over a period of time using the speed of the load, and several partial load signals (TL.sub.1, TL.sub.2) are used, the total thereof providing the load signal, a first partial load signal (TL.sub.1) displaying a maximum value as long as the load is fully on the weighing section of the scales (1), and a second partial load signal (TL.sub.2) displaying a minimum value as long as the load is completely removed from the weighing section of the scales (1), and the speed of the movement of the load is determined from said partial load signals (TL.sub.1 and TL.sub.2). The invention also relates to scales for carrying out said method, comprising two weighing units (10, 11) with flexible deformation elements on which deformation sensors (7, 15), which generate the partial load signals (TL.sub.1,TL.sub.2), are arranged.

The present disclosure relates to a method for computing a vehicle mass, a terminal device and a storage medium. The method includes: collecting engine torque data and electronic horizon data; determining whether two sampling points whose gradient value difference is greater than a gradient value difference threshold exist; determining whether the two sampling points are on a same road; determining whether the road between the two sampling points is a straight road; determining whether a difference between engine torques is greater than a torque difference threshold; calculating the vehicle mass according to the engine torques and gradient values corresponding to the two sampling points.