The present disclosure provides a method and system for controlling a four-wheel-independent-drive (4WID) electric vehicle (EV) which incorporates the method steps of: acquiring driving environmental information of the vehicle, running state information of the vehicle and driving expectation information of a driver; tracking a body attitude; switching a condition of the vehicle according to information of an upper module; calculating an expected longitudinal torque, an expected lateral torque and an expected yaw torque of the vehicle that meet a driver's expectation; optimally distributing the torques of the vehicle; and generating armature voltage signals required by output torques of motors and controlling the motors. The method divides the driving process of the vehicle into multiple independent driving conditions. The method does not globally implement operation and control in multiple driving conditions with a single control strategy, but coordinately switches the conditions according to multiple control modes and multiple control strategies.

The present disclosure provides a method and system for controlling a four-wheel-independent-drive (4WID) electric vehicle (EV) which incorporates the method steps of: acquiring driving environmental information of the vehicle, running state information of the vehicle and driving expectation information of a driver; tracking a body attitude; switching a condition of the vehicle according to information of an upper module; calculating an expected longitudinal torque, an expected lateral torque and an expected yaw torque of the vehicle that meet a driver's expectation; optimally distributing the torques of the vehicle; and generating armature voltage signals required by output torques of motors and controlling the motors. The method divides the driving process of the vehicle into multiple independent driving conditions. The method does not globally implement operation and control in multiple driving conditions with a single control strategy, but coordinately switches the conditions according to multiple control modes and multiple control strategies.

A yaw stability control system is provided for a motor vehicle. The system includes one or more cameras, a plurality of wheel speed sensors, a yaw angle sensor, and a steering angle sensor. The system further includes an electric motor connected to a reaction wheel. The system further includes a processor and a memory including instructions such that the processor is programmed to: determine a desired yaw angle of the motor vehicle based on a video signal, speed signals, a yaw signal, and a steering signal. The processor is further programmed to generate an actuation signal associated with the desired yaw angle. The electric motor angularly rotates the reaction wheel at a predetermined angular rate in a predetermined rotational direction to produce a counter-acting torque that rotates the motor vehicle to the desired yaw angle, in response to the electric motor receiving the actuation signal from the processor.

A method for controlling an interference torque for a vehicle is provided. The method is applied to a new energy vehicle including an electric motor and an engine, and includes steps of: arbitrating between a pedal torque of a driver and an interference torque required by ESP; performing an initial allocation on the electric motor and/or the engine in response to the pedal torque when the vehicle is in a hybrid drive mode, to meet an engine torque request while ensuring that the engine is operated at an optimal operation point; and determining, based on the initial allocation, whether the motor is capable of fully responding to the arbitrated torque, if so, controlling the motor to respond to the arbitrated torque in priority, otherwise controlling the engine and the motor to cooperatively respond to the arbitrated torque.

Disclosed is a driver assistance system including a camera installed in a vehicle, the camera having a field of view around the vehicle and obtaining an image data; and a controller configured to process the image data. The controller performs a lane keeping assistance control for providing an auxiliary steering torque to a steering actuator to maintain a driving lane of a vehicle. The controller changes at least one of a vehicle speed and the auxiliary steering torque depending on a payload of the vehicle during the lane keeping assistance control.

A system comprises a computer including a processor and a memory. The memory includes instructions such that the processor is programmed to: predict, at a trained machine learning classifier, a target slip value based on a predicted slip slope and a predicted road texture, wherein the predicted slip slope and the predicted road texture are determined using sensor data representing tire forces and modify at least one vehicle action based on the target slip value when a confidence level value corresponding to the target slip value is greater than or equal to a confidence level threshold.

A system comprises a computer including a processor and a memory. The memory includes instructions such that the processor is programmed to: predict, at a trained machine learning classifier, a target slip value based on a predicted slip slope and a predicted road texture, wherein the predicted slip slope and the predicted road texture are determined using sensor data representing tire forces and modify at least one vehicle action based on the target slip value when a confidence level value corresponding to the target slip value is greater than or equal to a confidence level threshold.

A vehicle includes a brake device, a suspension, and an electronic control unit configured to: control the brake device such that, in at least a part of a first range being a required deceleration range lower than a lower limit value of a vehicle deceleration perceivable by a person in the vehicle, a front-rear distribution ratio is constant regardless of the vehicle deceleration, and, in a second range in which the vehicle deceleration is higher than that in the first range, the front-rear distribution ratio is biased toward a rear wheel than in the first range; and in a specific deceleration range including the second range and higher than the first range, execute at least one of reducing a compression-side damping force of a front wheel damper compared with the first range and increasing an extension-side damping force of a rear wheel damper compared with the first range.

A vehicle includes a brake device, a suspension, and an electronic control unit configured to: control the brake device such that, in at least a part of a first range being a required deceleration range lower than a lower limit value of a vehicle deceleration perceivable by a person in the vehicle, a front-rear distribution ratio is constant regardless of the vehicle deceleration, and, in a second range in which the vehicle deceleration is higher than that in the first range, the front-rear distribution ratio is biased toward a rear wheel than in the first range; and in a specific deceleration range including the second range and higher than the first range, execute at least one of reducing a compression-side damping force of a front wheel damper compared with the first range and increasing an extension-side damping force of a rear wheel damper compared with the first range.

Disclosed are devices, systems and methods related to direct and indirect methods for detecting wind speed and direction during driving. An example method may include estimating, by a processor of a vehicle controller, a speed and a direction of wind movement near the vehicle based on a first sensor output from a wind sensor, or a second sensor output from a non-wind sensor, or a combination of the first sensor output and the second sensor output, wherein a primary purpose of the wind sensor is wind detection, and a primary purpose of the non-wind sensor is different from wind detection, and generating a control output indicative of a vehicle disturbance force resulting from the wind based on the estimated speed and direction of the wind movement.