A system of improved weighing utilizes accelerometers to compensate for measurement dynamics and non-level sensor orientation. Fill level of remote combines can be estimated by utilizing their historical harvesting performance and elapsed time or area harvested. Failure and degradation of weight sensors is detected by testing sensor half bridges. Loading and unloading weights can be tied to specific vehicles by utilizing RF beacons. Display location diversity is enhanced utilizing a mirror located as necessary while reversing the displayed image.

Controlling a maximum vehicle speed for an industrial vehicle includes determining, by a processor of the industrial vehicle, a torque applied to the traction wheel of the industrial vehicle; converting the torque to an equivalent force value; and determining an acceleration of the industrial vehicle while the torque is applied to the traction wheel. Additional steps include calculating a load being moved by the industrial vehicle, based at least in part on the acceleration and the equivalent force value; and controlling the maximum speed of the industrial vehicle based on the calculated load being moved by the industrial vehicle.

Various applications for use of mass estimations of a vehicle, including to control operation of the vehicle, sharing the mass estimation with other vehicles and/or a Network Operations Center (NOC), organizing vehicles operating in a platoon and/or partially controlling the operation of one or more vehicles operating in a platoon based on the relative mass estimations between the platooning vehicles. When vehicles are operating in a platoon, the relative mass between a lead and a following vehicle may be used to scale torque and/or brake commands generated by the lead vehicle and sent to the following vehicle.

A system of improved weighing utilizes accelerometers to compensate for measurement dynamics and non-level sensor orientation. Fill level of remote combines can be estimated by utilizing their historical harvesting performance and elapsed time or area harvested. Failure and degradation of weight sensors is detected by testing sensor half bridges. Loading and unloading weights can be tied to specific vehicles by utilizing RF beacons. Display location diversity is enhanced utilizing a mirror located as necessary while reversing the displayed image.

A dynamic calculation method and device of electric vehicle mass includes acquiring status data of a vehicle to be measured during an accelerating driving period, the status data including time, speed, height, gravitational acceleration, effective driving power and resistance power; according to the status data information, calculating the total output work, the total resistance work, the total potential energy change amount and the kinetic energy change amount of the vehicle to be measured during the accelerating driving period. Calculating, on the basis of the total output work of a vehicle drive motor being equal to the sum of the total resistance work, a total potential energy change amount of the vehicle in height and the kinetic energy change amount of the vehicle, the mass of the vehicle to be measured.

Various applications for use of mass estimations of a vehicle, including to control operation of the vehicle, sharing the mass estimation with other vehicles and/or a Network Operations Center (NOC), organizing vehicles operating in a platoon and/or partially controlling the operation of one or more vehicles operating in a platoon based on the relative mass estimations between the platooning vehicles. When vehicles are operating in a platoon, the relative mass between a lead and a following vehicle may be used to scale torque and/or brake commands generated by the lead vehicle and sent to the following vehicle.

A method is for determining a tire characteristic influencing variable and includes: a) detecting an acceleration of a measurement point on a tire inner side of a vehicle tire, wherein a deviation, caused by contact of the vehicle tire with a roadway, of the acceleration of the measurement point within an observation window is detected, b) deriving at least one analytical characteristic variable which is characteristic of the detected acceleration, wherein the at least one analytical characteristic variable characterizes the non-periodic profile of the detected acceleration within one tire rotation, c) determining at least one tire characteristic influencing variable in a manner dependent on the at least one analytical characteristic variable, wherein a mathematical mapping yields the dependency between the analytical characteristic variable and the tire characteristic influencing variable, wherein the mathematical mapping assigns at least one tire characteristic influencing variable to the at least one derived analytical characteristic variable.

An apparatus and method for determining the total weight of a vehicle either statically or dynamically using the same weight scale. The apparatus is a weight scale for weighing vehicles that is of sufficient length that a plurality of axle sets of a vehicle can be located on the weight scale simultaneously. The apparatus senses the total weight of the vehicle as a function of time within the period of time the vehicle is on the weight scale. The apparatus obtains the vehicle weight statically if all of the axle sets of a vehicle are located on the weight scale simultaneously and the vehicle is in a stopped condition and obtains the vehicle weight dynamically if all of the axle sets of the vehicle are located on the weight scale simultaneously and the vehicle is moving on the weight scale.

A system and a method which determines the mass of a ship moving in water, comprising at least two gravitational field strength sensor units that are stationary relative to the ship at a known distance from each other, and an analytical unit which determines the mass of the ship based of measurement signals acquired by the at least two GFS sensor units.

Realized is a technique for estimating a state quantity of a vehicle, which technique is applicable to estimation of a vehicle weight and allows an increase in accuracy and speed of the estimation. A state quantity estimating device includes a data storing section (101), a predictive quantity computing section (102), an obtaining section (107), a Kalman gain computing section (103), an estimated quantity computing section (104) which calculates an estimated state quantity and estimated covariance, and a process noise covariance correcting section (106) which corrects process noise covariance. The estimated state quantity, the estimated covariance, and the process noise covariance, each of which has been calculated or corrected, are written in the data storing section (101) as a state quantity, state covariance, and process noise covariance, respectively, and are used in a next computation for estimating a state quantity.