A monitoring system and method determine a consumption metric representative of one or more of an amount of fuel consumed or an amount of energy consumed by a vehicle during travel over a route. The consumption metric is independent of one or more of vehicle load or elevation change over the route. The system and method optionally can determine a route condition metric representative of a condition of a route traveled upon by a vehicle. The route condition metric is based on a comparison between an actual grade of the route at one or more locations along the route and an estimated grade of the route at the one or more locations.

Methods, apparatuses, computer program products, systems for estimating a tire operating efficiency and range of an electric vehicle are disclosed. In a particular embodiment, a method includes determining a tire load parameter for a tire based in part on a tire deformation parameter generated by a tire mounted sensor (TMS); determining a coefficient of rolling resistance parameter for the tire based in part on a tire pressure measurement and a linear velocity measurement; and determining, based on the tire load parameter and the coefficient of rolling resistance parameter, a force of rolling resistance parameter for the tire.

A system for controlling platooning by a following vehicle includes a main body of the following vehicle. The system further includes a pressure sensor located in or on the main body and configured to detect a pressure corresponding to a pressure wake from a leading vehicle. The system further includes an electronic control unit (ECU) located in or on the main body, coupled to the pressure sensor, and configured to determine an optimal distance from the following vehicle to the leading vehicle based on the detected pressure. The optimal distance corresponding to a distance at which drag applied to the following vehicle is reduced based on the pressure wake from the leading vehicle.

A system for controlling platooning by a following vehicle includes a sensor located in or on the following vehicle configured to detect data corresponding to a shape of a leading vehicle. The system further includes an electronic control unit (ECU) located in or on the following vehicle, coupled to the sensor, and configured to determine an optimal distance from the following vehicle to the leading vehicle based on the shape of the leading vehicle, the optimal distance corresponding to a distance at which drag applied to the following vehicle is reduced based on a pressure wake from the leading vehicle.

A vehicle drive route instruction system in a hybrid vehicle in which when it is judged that currently the vehicle is driving through the inside of the engine drive restriction zone where driving by the internal combustion engine is restricted, the internal combustion engine is made to stop operating, the electric motor is used to drive the vehicle, and the shortest route from the current position to the boundary of the inside of the engine drive restriction zone and the outside of the engine drive restriction zone is searched. When it is judged that the SOC amount will fall to the preset judgment standard when driving the vehicle through the searched shortest route from the current position to the boundary, an occupant of the vehicle is given information to guide the vehicle from the current position through the searched shortest route to the boundary.

An embodiment acceleration limit control method includes determining an acceleration limit based on information on a passenger, determining a disturbance torque due to a disturbance, other than a drive source of a vehicle, based on at least a slope, determining a torque limit satisfying the acceleration limit based on the disturbance torque, and determining an output torque to be generated by the drive source based on the torque limit and a driver's requested torque.

A vehicle and a method of calculating a load therefor for calculating a driving load based on a weather condition are provided. The method includes acquiring weather information regarding rain or snow and calculating a first driving load applied to an upper surface portion of the vehicle based on the weather information. A second driving load applied to a front surface portion of the vehicle is calculated based on the weather information and a third driving load that is a driving load due to weather is calculated by summing the first driving load and the second driving load.

An apparatus comprising an interface, a memory and a processor. The interface may be configured to receive sensor data samples during operation of a vehicle. The memory may be configured to store the sensor data samples over a number of points in time. The processor may be configured to analyze the sensor data samples stored in the memory to detect a pattern. The processor may be configured to manage an application of brakes of the vehicle in response to the pattern.

The present disclosure relates to improvements in the stability of work machines. A method for predicting a risk of instability for one or more work machine(s) moving along a route along terrain of a worksite is provided. Ground condition data indicative of the ground condition of the terrain along the route is obtained. Surface topography data indicative of the surface topography of the terrain along the route is obtained. Route data indicative of the route along the terrain is generated. The ground condition data, the surface topography data and the route data are processed to generate risk data indicative of a risk of instability along the route.

Various embodiments include a method for determining an effective wind speed to which a vehicle is exposed while driving comprising: determining an effective mechanical drive power for the vehicle by measuring the current and voltage at an electric motor and using an efficiency characteristic diagram of the electric motor and accounting for losses in a drive train of the motor vehicle; and calculating the effective wind speed based on the effective mechanical drive power.