A four-wheel drive vehicle includes a drive-power distribution device including (a) a clutch for distributing an engine drive power, between main and auxiliary drive wheels, (b) an electric motor, (c) a press mechanism for pressing the clutch by converting a rotary motion of the electric motor into a linear motion. The drive-power distribution device adjusts a torque capacity of the clutch to adjust a drive-power distribution ratio between the main and auxiliary drive wheels. The vehicle further includes a control apparatus for executing a drive-power distribution control for adjusting the drive-power distribution ratio, and an automatic-stop control for causing the engine to be automatically stopped upon satisfaction of an engine-stop condition. When the engine is in a stop state by execution of the automatic-stop control, the control apparatus inhibits change of the drive-power distribution ratio which is to be made by change of a rotational direction of the electric motor.

A method of controlling an axle assembly includes providing an axle assembly in a first state. A first controller is provided in electrical communication with the axle assembly. The first controller determines if a source of power has an available amount of electrical energy that is within a predetermined range and a predetermined period of time has elapsed. If the available amount of electrical energy is within the predetermined range and the predetermined period of time has elapsed, then electrical energy is transferred from the source of power to an electric motor generator and an axle disconnect clutch is engaged to provide the axle assembly in another state.

A system for supervisory control for eAWD and eLSD in a motor vehicle includes a control module, and sensors and actuators disposed on the motor vehicle. The sensors measure real-time motor vehicle data, and the actuators alter behavior of the motor vehicle. The control module receives the real-time data; receives one or more driver inputs to the motor vehicle; determines a status of a body of the motor vehicle; determines a status of axles of the motor vehicle; determines a status of each wheel of the motor vehicle; and generates a control signal to the actuators from the driver inputs and the body, axle, and wheel statuses. The control module also exercises supervisory control by actively adjusting constraints on the control signal to each of the actuators where actively adjusting constraints on the control signal alters boundaries of control actions in response to the one or more driver inputs.

A method for controlling actuators acting on vehicle wheels of a motor vehicle comprises ascertaining a force to be brought about on a reference point of the motor vehicle on the basis of driver specifications, ascertaining wheel forces to be brought about on the vehicle wheels to implement the force to be brought about on the reference point of the motor vehicle by means of a first dynamic allocation by model-based predictive control (MPC), ascertaining setpoint values for wheel parameters from the ascertained wheel forces, and actuating the actuators of the motor vehicle so as to implement the setpoint values of the wheel parameters.

Provided are methods for controlling ESA system of a vehicle and an ESA system. The method includes: generating a trajectory to avoid an obstacle in front of the vehicle; obtaining a target yaw rate and yaw moment according to the trajectory; allocating the target yaw moment to one or more chassis actuators; controlling the one or more chassis actuators according to allocated yaw moments. The cooperation of actuators is implemented for more safe evasion.

A control allocation system for a vehicle includes an electric power steering (EPS) system, one or more redundant actuation systems for controlling a plurality of wheels of the vehicle, and one or more controllers in electronic communication with the EPS system and the one or more redundant actuation systems. The one or more controllers execute instructions to determine tracking errors and vehicle dynamics states based on a plurality of local path planning references and receive a fault signal indicating the EPS system is non-functional. In response to receiving the fault signal, the one or more controllers determine a plurality of corrective constraints in real-time. The one or more controllers solve a real-time constrained optimization problem for each sampling interval of the control allocation system to determine a plurality of control actions based on the plurality of corrective constraints and the tracking errors.

A method for controlling the traveling of a vehicle includes determining, by a control unit, a basic torque command based on vehicle operating information collected during traveling of a vehicle; obtaining, by the control unit, vertical load information of a left wheel and a right wheel of the vehicle in real time during traveling of the vehicle based on information collected in the vehicle; determining, by the control unit, a partial braking amount from the determined real-time basic torque command and the obtained real-time vertical load information; and performing, by the control unit, a partial braking control controlled by an inner wheel braking device so that a braking force corresponding to the partial braking amount is applied to a turning inner wheel among the left wheel and the right wheel.

Hybrid-electric powertrain control systems and methods include a set of sensors configured to measure a set of operating parameters of a set of components of the hybrid-electric powertrain that are each a constraint on minimum/maximum motor torque limits for the electric motors thereby collectively forming a set of constraints and a controller configured to perform a linear optimization to find the best engine torque values that are attainable subject to a set of constraint inequalities as defined by current vehicle state and as monitored by the set of sensors, and control the hybrid-electric powertrain based on the best engine torque values to avoid excessive torque commands that could damage physical components of the hybrid-electric powertrain and/or could cause undesirable noise/vibration/harshness (NVH) characteristics.

An apparatus with torque vectoring control of a vehicle with an independent driving motor includes: one or more processors configured to: measure driving information including a steering angle, a yaw rate, a longitudinal velocity, lateral acceleration and longitudinal acceleration of the vehicle; calculate a driving aggressiveness (DA) index representing driving aggressiveness of a driver through an exponential weighted moving average (EWMA) operation using the driving information; calculate a target yaw rate based on the driving information and the DA index; and generate a control moment based on the driving information, the DA index and the target yaw rate, wherein, for the calculating of the DA index, the one or more processor are configured to calculate the DA index to have a higher value than a case of generating only longitudinal acceleration or a case of generating only lateral acceleration, in response to the longitudinal acceleration and the lateral acceleration being generated at a same time.

A method for determining a load distribution in a powertrain of a motor vehicle, whereby the powertrain has at least two drive machines, whereby the first drive machine is provided for a front-wheel drive and the second drive machine is provided for a rear-wheel drive, whereby the method comprises: determining a load distribution characteristic map that is based on a first efficiency characteristic map of the first drive machine and on a second efficiency characteristic map of the second drive machine.