Methods and systems for estimating an axle load of a vehicle are described. In one example, a method is disclosed wherein axle load is estimated in response to an angle between two components of an axle. The angle may change as weight is added to or removed from the axle such that axle load may be determined as a function of the angle.

A power adjustment system and a power adjustment method of an autonomous mobile device are provided. In the power adjustment method, two first current control signals respectively transmitted to two drivers are outputted by a control module. A tilt angle of the autonomous mobile device is detected by an inertial measurement module. A travel route is planned by a navigation module, and the control module obtains a steering angle of the autonomous mobile device during a traveling process. According to different weight values of the autonomous mobile device stored in a database module, a weight of the autonomous mobile device is estimated by the control module. According to the two first current control signals and the weight, the steering angle, and the tilt angle of the autonomous mobile device, two second current control signals respectively transmitted to the two drivers are outputted by the control module.

The present invention discloses an intelligent vehicle platoon lane change performance evaluation method. First, an intelligent vehicle platoon lane change performance test scenario is established; secondly, a three-degree of freedom nonlinear dynamics model is established according to motion characteristics of intelligent vehicles in a platoon lane change process; further, an improved adaptive unscented Kalman filter algorithm is utilized to perform filter estimation on state variables of positions and velocities of platoon vehicles; and finally, based on accurately recursive vehicle motion state parameters, evaluation indexes for platoon lane change performance are proposed and quantified, and an evaluation system for platoon lane change performance is constructed. According to the method proposed in the present invention, the problem of lacking platoon lane change performance quantitative evaluation at present is solved, vehicle motion state parameters can be measured in a high-precision and comprehensive manner, multi-dimensional platoon lane change performance evaluation indexes are quantified and output, and comprehensive, accurate, and reliable scientific quantitative evaluation for platoon lane change performance is achieved.

The present invention discloses an intelligent vehicle platoon lane change performance evaluation method. First, an intelligent vehicle platoon lane change performance test scenario is established; secondly, a three-degree of freedom nonlinear dynamics model is established according to motion characteristics of intelligent vehicles in a platoon lane change process; further, an improved adaptive unscented Kalman filter algorithm is utilized to perform filter estimation on state variables of positions and velocities of platoon vehicles; and finally, based on accurately recursive vehicle motion state parameters, evaluation indexes for platoon lane change performance are proposed and quantified, and an evaluation system for platoon lane change performance is constructed. According to the method proposed in the present invention, the problem of lacking platoon lane change performance quantitative evaluation at present is solved, vehicle motion state parameters can be measured in a high-precision and comprehensive manner, multi-dimensional platoon lane change performance evaluation indexes are quantified and output, and comprehensive, accurate, and reliable scientific quantitative evaluation for platoon lane change performance is achieved.

An embodiment inter-platooning vehicle distance controller includes a processor configured to separate a linear control section from a non-linear control section based on whether a preceding vehicle brakes during platooning, predict a real-time deceleration for each platooning vehicle with regard to a disturbance factor when generating a deceleration in the linear control section, and set target decelerations of platooning vehicles based on the predicted real-time deceleration, and a memory configured to store data and an algorithm executable by the processor.

An embodiment inter-platooning vehicle distance controller includes a processor configured to separate a linear control section from a non-linear control section based on whether a preceding vehicle brakes during platooning, predict a real-time deceleration for each platooning vehicle with regard to a disturbance factor when generating a deceleration in the linear control section, and set target decelerations of platooning vehicles based on the predicted real-time deceleration, and a memory configured to store data and an algorithm executable by the processor.

A fuel efficiency score management device includes: an acquisition section configured to acquire driving information as detected during driving by a sensor unit installed at a vehicle; a fuel efficiency scoring section configured to decide a fuel efficiency score corresponding to a reduction in carbon dioxide emissions based on the acquired driving information; a score storage section configured to store the fuel efficiency score; and an incentive awarding section configured to lower a usage fee for the vehicle according to the stored fuel efficiency score.

A fuel efficiency score management device includes: an acquisition section configured to acquire driving information as detected during driving by a sensor unit installed at a vehicle; a fuel efficiency scoring section configured to decide a fuel efficiency score corresponding to a reduction in carbon dioxide emissions based on the acquired driving information; a score storage section configured to store the fuel efficiency score; and an incentive awarding section configured to lower a usage fee for the vehicle according to the stored fuel efficiency score.

A control apparatus for a vehicle includes: a target yaw rate calculator; a primary limit yaw rate calculator; a yaw rate comparator; a secondary limit yaw rate calculator; and a vertical load controller. The target yaw rate calculator calculates a target yaw rate of the vehicle. The primary limit yaw rate calculator calculates a primary limit yaw rate on a basis of a vertical load on a wheel. The yaw rate comparator compares the target yaw rate with the primary limit yaw rate. The secondary limit yaw rate calculator calculates a secondary limit yaw rate in a case where a distribution of the vertical load on the wheel is changed in a case where the target yaw rate exceeds the primary limit yaw rate. The vertical load controller changes the vertical load on a basis of the secondary limit yaw rate.

A control apparatus for a vehicle includes: a target yaw rate calculator; a primary limit yaw rate calculator; a yaw rate comparator; a secondary limit yaw rate calculator; and a vertical load controller. The target yaw rate calculator calculates a target yaw rate of the vehicle. The primary limit yaw rate calculator calculates a primary limit yaw rate on a basis of a vertical load on a wheel. The yaw rate comparator compares the target yaw rate with the primary limit yaw rate. The secondary limit yaw rate calculator calculates a secondary limit yaw rate in a case where a distribution of the vertical load on the wheel is changed in a case where the target yaw rate exceeds the primary limit yaw rate. The vertical load controller changes the vertical load on a basis of the secondary limit yaw rate.