A hybrid all-wheel-drive vehicle includes an engine, first and second motor generators, a first clutch between the second motor generator and a front wheel, a second clutch between the second motor generator and a rear wheel, and a control unit that controls, based on a vehicle traveling state, the engine, the motor generators, and the clutches. The first motor generator is coupled to the engine and the front wheel in a manner capable of transmitting torque. During regeneration, the control unit engages the first clutch and disengages the second clutch. When the all-wheel-drive vehicle shifts from motor traveling to hybrid traveling, the control unit restarts the engine by operating the first motor generator and regulates engagement forces of the clutches and output torque of the second motor generator to compensate driving torque of the front wheel by the second motor generator while maintaining driving torque of the rear wheel.

A method includes identifying sensor data associated with corresponding distal ends of one or more axles of an autonomous vehicle (AV). The method further includes determining, based on the sensor data, mass distribution data of the AV. The mass distribution data is associated with a first load proximate a first distal end of a first axle of the AV and a second load proximate a second distal end of the first axle of the AV. The method further includes causing, based on the mass distribution data, performance of a corrective action associated with the AV.

An arithmetic model generation system includes a sensor information acquisition unit, a tire force calculator, and an arithmetic model update unit. The sensor information acquisition unit acquires acceleration of a tire. The tire force calculator includes an arithmetic model for calculating tire force F based on the acceleration, and calculates the tire force F by inputting the acceleration acquired by the sensor information acquisition unit. The arithmetic model update unit compares tire axial force measured by the tire and the tire force F calculated by the tire force calculator, and updates the arithmetic model.

Mappings of keys to actions can automate various vehicle systems. Some automations can provide lane departure warnings. Keys for lane departure mappings can specify vibration patterns expected when a vehicle drives over lane delineators. These vibration-based mappings can include keys with vibration patterns, e.g., defining vibration frequencies or vibration locations. Keys for emergency light mappings can be based on conditions such as (1) the vehicle being on the road, stopped, not in traffic, and not at a stop signal; (2) components of the vehicle having failed; or (3) weather conditions.

Disclosed is a vehicle control method which comprises the steps of: determining whether or not a squat of a rear end of a vehicle body is equal to or greater than a given level; determining whether or not turning manipulation of a steering device has been made; and, when the turning manipulation of the steering device is determined to have been made, controlling each part of an engine (4) to reduce an output torque of the engine (4), wherein, in response to the determination that the turning manipulation of the steering device has been made, a reduction amount of the output torque of the engine is increased when the squat of the rear end of the vehicle body is equal to or greater than the given level, as compared to when the squat is less than the given level.

A method for estimating a friction between a road surface and a tire of a steered wheel of a vehicle. The steered wheel being fit with dynamic steering. The vehicle includes a steering wheel and a set of sensors comprising wheel end sensors and steering wheel sensors configured to measure signals corresponding to a set of parameters., The steering wheel parameters comprising at least a steering wheel torque and a steering wheel angle. The method comprising the following steps implemented by the electronic control unit collect the signals, corresponding to the set of parameters, measured by the sensors during a period of time; process, by the signal processing module, the signals collected to provide processed signal data provide the processed signal data as input to the wheel end friction estimation model, the wheel end friction estimation model being configured to output a friction estimation of the friction between the road surface and the tire of the wheel.

Embodiments of the present application disclose a safety control method and a safety control system based on environmental risk assessment for an intelligent connected vehicle. The method includes: when a vehicle is in an automatic driving mode, acquiring environmental parameter information of the vehicle in a current driving environment; determining a target driving control parameter which meets a preset safe driving condition under the current environmental parameter; and managing a current automatic driving level of the vehicle by using the target driving control parameter.

A method and a device for determining loads on vehicle's wheels, each with a tire, is disclosed. A deformation measured value and a pressure measured value for each tire, and at least one acceleration measured value for the vehicle are detected. For the respective wheels, dynamic wheel loads are calculated according to a first model and static wheel loads are calculated according to a second model. The second model comprises at least one model parameter calculated by statistical analysis of the calculated dynamic wheel loads, the calculated static wheel loads, and the detected at least one acceleration measured value. The at least one acceleration measured value is redetected and the dynamic wheel loads are recalculated from the previously calculated static wheel loads and the at least one detected acceleration measured value according to the second model using the previously calculated at least one model parameter of the second model.

Techniques are described for determining weight distribution of a vehicle. A method of performing autonomous driving operation includes determining a vehicle weight distribution that values for each axle of the vehicle that describe weight or pressure applied on a respective axle. The values of the vehicle weight distribution are determined by removing at least one value that is outside a range of pre-determined values from a set of sensor values. The method further includes determining a driving-related operation of the vehicle weight distribution. For example, the driving-related operation may include determining a braking amount for each axle and/or determining a maximum steering angle to operate the vehicle. The method further includes controlling one or more subsystems in the vehicle via an instruction related to the driving-related operation. For example, transmitting the instruction to the one or more subsystems causes the vehicle to perform the driving-related operation.

A vehicle includes a center differential device and an air pressure controller. The center differential device includes a first output shaft coupled to front wheels and a second output shaft coupled to rear wheels. The center differential device is configured to perform differential operation between the first output shaft and the second output shaft and to limit the differential operation between the first output shaft and the second output shaft. The air pressure controller is configured to control air pressure of one or more tires of the front wheels and the rear wheels such that an average rotational speed of the front wheels and an average rotational speed of the rear wheels are equal to each other.