A device for controlling, in real time, the trajectory of an autonomous vehicle includes a control module which produces, in real time, from a state vector at each point in time, a first steering command in order to stabilize the trajectory of the vehicle relative to a vehicle path. The device includes an anticipation module which generates a variable representative of a meta-vector of deviations for each predicted position of the vehicle at points in time resulting in a given quantity at the current point in time and of the state vector at the current point in time. The control module produces the first steering command by quadratic optimization of a relationship between the generated representative variable and a meta-vector of successive steering commands for each predicted position of the vehicle at points in time resulting in a given quantity at the current point in time.

Methods and devices for adapting a gain factor of an acceleration controller for a motor vehicle are provided. An acceleration controller specifies an acceleration setpoint for the motor vehicle in a time increment. The acceleration setpoint is specified as a function a speed setpoint of the motor vehicle, an actual speed of the motor vehicle, and the gain factor. The device stores the speed setpoint, the actual speed, and the acceleration setpoint specified as information for at least two time increments, select a first subset of the information, and train a model as a function of the first subset. The model predicts an actual speed in a later time increment from at least one stored actual speed and at least one stored acceleration setpoint, select a second subset of the information, and adapt the gain factor as a function of the second subset, the model and the acceleration controller.

A number of illustrative variations may include a system including brake-to-steer algorithms may achieve lateral control of a vehicle without longitudinal compensation but may also force a vehicle to slow down too rapidly before appropriate lateral movement can be achieved and may deliver an unnatural driving experience for vehicle occupants. A more natural feeling deceleration may be achieved by optimally selecting appropriate transmission shifts to allow for optimal engine speed or electric motor speed and torque based on current vehicle speed thereby reducing undesirably longitudinal disturbance.

Systems and methods are provided herein for controlling the speed on each wheel of a vehicle, possibly operating a vehicle in a speed control mode. In response to receiving input to engage speed control mode and receiving an accelerator pedal input, the system determines a target wheel speed based on the accelerator pedal input, monitors wheel speed of each of a plurality of wheels and determines, for each monitored wheel, a difference based on the monitored wheel speed and the target wheel speed. A torque is provided to each of the plurality of wheels based on the respective difference to achieve the target wheel speed.

Methods and systems are provided for increasing an efficiency of a modular hybrid transmission (MHT) of a hybrid vehicle. In one example, a method for operating an MHT comprises, at one or more control modules, determining an upper torque bound and a lower torque bound of a feedback controller based on a feedforward (FF) engine torque value, the feedback controller controlling a torque of an electric motor of the hybrid vehicle; and constraining operation of the electric motor via the feedback controller based on the upper and lower torque bounds. The electric motor may be controlled by a hybrid powertrain control module of the MHT. The upper and lower torque bounds may be calculated at a powertrain control module of the MHT based on torque converter losses.

An automotive vehicle control circuit can include a PID Controller that receives at an input a set point signal for the closed-loop control system and provides as an output a control signal that is fed to the motion control system. The PID controller is arranged in a closed-loop configuration with the motion control system to minimise an error value indicative of the difference between the demanded behaviour of the motion control system as indicated by the demand signal and the actual behaviour of the motion control system. The control circuit can include a neural network which has an input layer of neurons, at least one hidden layer of neurons, and an output layer comprising at least one output neuron, in which the neural network comprises a feedforward neural network that receives at the input layer of input neurons the demand signal, the drive signal output from the controller and the error value. The neural network is configured to determine one or more of the P gain, I gain and D gain terms used by the PID controller, and the neural network receives as a feedforward term at least one additional discrete environmental variable.

A vehicle control device includes a controller configured to control operation of a driving motor that is to output a driving force for a vehicle. The controller is switchable between a normal mode of controlling acceleration/deceleration based on a driver's acceleration/deceleration operation, and a cruise control mode of maintaining the vehicle speed at a target speed without the acceleration/deceleration operation. The controller is configured to, during the cruise control mode, calculate a torque command value for the motor by using integral control based on an integrated value of a deviation between the vehicle speed and the target speed, and execute an integrated-value adjustment process if the controller determines that the vehicle entered a flat road or an uphill road from a downhill road or a downhill road from a flat road or an uphill road. The process adjusts the integrated value to reduce an absolute value of the integrated value.

A method for having a vehicle follow a desired curvature path is provided. The vehicle has at least one differential with a differential lock connected to at least one driven wheel axle of the vehicle. The method includes providing information regarding state of the differential lock, the state being either that the differential lock is activated or unlocked, and when the differential lock is activated, calculating a yaw moment of the vehicle caused by the differential lock; and compensating for a deviation from the desired curvature path caused by the yaw moment such that a resulting steering angle is equal to or less than a maximum allowed steering angle of the vehicle. The compensation is a feed forward compensation.

Embodiments described herein improve fuel economy by controlling a vehicle powertrain based on a predicted vehicle velocity. The vehicle velocity is predicted based on vehicle-to-vehicle data when a prediction horizon is a longer prediction horizon and the vehicle velocity is predicted based on historical drive cycle data when the prediction horizon is a shorter prediction horizon. A time duration of the shorter prediction horizon is shorter than the time duration of the longer prediction horizon. A plurality of drive cycles are established for both the longer and the shorter prediction horizons using a neural network. A shorter prediction horizon drive cycle uses nonlinear autoregressive exogenous model neural networks and the longer prediction horizon drive cycle uses two layer feedforward neural networks. The predicted vehicle velocity is determined from a similar drive cycle of the plurality of drive cycles of either the shorter and/or the longer prediction horizon drive cycles.

Provided are a driving force control method and device for a hybrid vehicle, each capable of effectively absorbing torque fluctuation of an engine while suppressing deterioration in energy efficiency. The driving force control device for a hybrid vehicle comprises a PCM configured to: identify a vehicle acceleration; estimate an average torque output by an engine; estimate a torque fluctuation component of the torque output by the engine; set a countertorque for suppressing the estimated torque fluctuation component; and control an electric motor to output the set countertorque, wherein the PCM is operable, under a condition that an engine speed and the average torque output by the engine are constant, to set the countertorque such that, as the absolute value of the vehicle acceleration becomes smaller, the absolute value of the countertorque becomes larger.