An automatic torque control system and methods for automatically controlling a torque of a vehicle are disclosed. The method includes detecting when the vehicle engages a load. The method further includes automatically decreasing the torque when the vehicle engages the load and prior to one or more wheels of the vehicle slipping.

Method and apparatus are disclosed for traction control based on friction coefficient estimation. An example vehicle includes a plurality of sensors to measure qualities of a surface of a road and an anti-lock brake system module. The anti-lock brake system module (a) estimates confidence values for different road surface types based on the qualities of the surface of the road, (b) estimates a coefficient of friction between the road and tires of the vehicle based on the confidence values, and (c) adapt a traction control system by altering a target slip based on the coefficient of friction.

A vehicle control system to be mounted in a hybrid electric vehicle includes an engine, a center differential that includes a front-wheel-side output portion and a rear-wheel-side output portion and distributes torque outputted from the engine to a front wheel and a rear wheel, a limited slip differential mechanism that limits a differential between the front-wheel-side output portion and the rear-wheel-side output portion, and a motor disposed in a drive-power transferring system that transfers drive power from the rear-wheel-side output portion to the rear wheel. The vehicle control system includes a processor. When the hybrid electric vehicle is switched from a first traveling mode to a second traveling mode, the processor stops the engine while causing the limited slip differential mechanism to limit the differential between the front-wheel-side output portion and the rear-wheel-side output portion.

A safety system for a vehicle may include one or more processors configured to determine, based on a friction prediction model, one or more predictive friction coefficients between the ground and one or more tires of the ground vehicle using first ground condition data and second ground condition data. The first ground condition data represent conditions of the ground at or near the position of the ground vehicle, and the second ground condition data represent conditions of the ground in front of the ground vehicle with respect to a driving direction of the ground vehicle. The one or more processors are further configured to determine driving conditions of the ground vehicle using the determined one or more predictive friction coefficients.

A method for planning a vehicle trajectory includes: acquiring an initial reference trajectory of a target vehicle within a target planning duration, the initial reference trajectory including an initial state variable and an initial control variable of the target vehicle at at least one position point within the target planning duration; acquiring a reference lane trajectory; determining a trajectory cost of the target vehicle according to a geometric constraint and a dynamics constraint by using the reference lane trajectory and the initial state variable and the initial control variable of the target vehicle at the at least one position point, the dynamics constraint including at least one of an energy loss, an acceleration constraint, or an angular speed constraint; and adjusting the initial reference trajectory of the target vehicle to a target travelling trajectory according to the trajectory cost of the target vehicle.

When a speed difference between a maximum rotation speed and an engine rotation speed, that is, an actual rotation speed difference, is equal to or less than a margin rotation speed difference, an engine operating point is changed such that the actual rotation speed difference becomes greater than the margin rotation speed difference. Accordingly, the speed difference between the maximum rotation speed and the engine rotation speed is prevented from becoming equal to or less than the margin rotation speed difference. As a result, since a relatively sufficient margin is secured in the difference between the maximum rotation speed and the engine rotation speed, it is possible to prevent the engine rotation speed from falling into a high-rotation state in which the engine rotation speed exceeds the maximum rotation speed.

A method for adaptive estimation of a road surface adhesion coefficient for a vehicle with complex excitation conditions taken into consideration comprises the following steps: 1) designing an estimator according to a single-wheel dynamics model of a vehicle, and estimating a longitudinal tire force and a road surface peak adhesion coefficient under longitudinal excitation; 2) designing an estimator according to a two-degree-of-freedom kinematic model of the vehicle, and estimating a tire aligning moment and a road surface peak adhesion coefficient under excitation of a lateral force; and 3) determining an excitation condition met by the vehicle according to a vehicle state parameter, performing fuzzy inference to obtain limits achievable by current longitudinal and lateral tire forces, and designing a fusion observer to fuse estimation results. The method achieves favorable robustness, improves real-time capability, and can be performed quickly and accurately.

An estimation apparatus performs non-contact estimation of a friction coefficient of a road surface. The estimation apparatus includes at least one processor. The processor determines a state of the road surface and determine which of preset road-surface states the state of the road surface belongs to. The processor performs primary identification of a first range of a friction coefficient corresponding to the determined road-surface state on the basis of friction coefficient information and the determined state of the road surface. The friction coefficient information is sectioned for each of the road-surface states. The processor narrows down a range of the friction coefficient from the first range to a second range on the basis of the identified first range of the friction coefficient, and thereby perform secondary identification of the friction coefficient of the road surface. The second range is narrower than the first range.

A controller is provided for a vehicle having front and rear axles, each axle having two wheels, and first and second propulsion units. The controller controls the first and second propulsion units to generate a combined torque with reference to a total requested torque. The controller is configured to: receive a torque request signal; receive traction signals indicating available traction at at least one wheel; determine a traction torque range defined by a maximum and minimum torque for at least one of the at least first or second propulsion units in dependence on one or more of the traction signals; determine a proposed distribution of torque between each of the at least first and second propulsion units with reference to the total requested torque; and determine a proposed torque to be generated by each of the at least first and second propulsion units based on the proposed distribution of torque.

A vehicle control apparatus to be applied to a vehicle includes a first traveling motor, a second traveling motor, and a control system. The control system estimates a first friction coefficient between a first wheel and a road surface and a second friction coefficient between a second wheel and a road surface. When the vehicle starts in a situation in which any of the first and second friction coefficients is less than a first threshold and a difference between the first and second friction coefficients is greater than a second threshold, the control system increases a power running torque of the first traveling motor after elapse of a first delay time after increasing a power running torque of the second traveling motor, if the first friction coefficient is smaller than the second friction coefficient. The first delay time is set on the basis of the first friction coefficient.