625 results about "Slip angle" patented technology

A vehicle dynamics behavior reproduction system capable of describing accurately behavior of a motor vehicle in a lateral direction even for nonlinear driving situation includes a vertical wheel force arithmetic means (105), a lateral wheel force arithmetic means (110), a cornering stiffness adaptation means (115), a state space model/observer unit (120), a selector (130), a delay means (135), and a tire side slip angle arithmetic means (125). Vertical wheel forces (F_Zij) and tire side slip angles (α_ij) are determined by using sensor information and estimated values while lateral wheel forces (F_Yij) are determined in accordance with a relatively simple nonlinear approximation equation. The lateral wheel force (F_Yij) and the tire side slip angle (α_ij) provide bases for adaptation of cornering stiffnesses at individual wheels. Vehicle motion is accurately described to a marginal stability by using adapted cornering stiffnesses (C_ij) and other information.

An improved vehicle active brake control based on an estimate of vehicle yaw rate and slip angle, wherein the estimate is based on a weighted average of two yaw rate values developed with two different estimation techniques. In general, the first estimate of yaw rate is based on the relative velocity of the un-driven wheels, and the second estimate is based on a measure of lateral acceleration. Confidence levels in each estimate are determined and used to form a third or preliminary yaw rate estimate based on a weighted average of the first and second estimates, and the third estimate is supplied to a closed-loop nonlinear dynamic observer which develops the final estimate of yaw rate, along with estimates of lateral velocity and side-slip angle.

A system and method of controlling a vehicle with a trailer comprises determining the presence of a trailer, determining a vehicle velocity, determining a steering wheel angle, and determining a rear axle side slip angle. When the rear axle side slip angle is above a predetermined value, the vehicle velocity is above a velocity threshold, and the steering wheel is about zero, brake-steer is applied to the vehicle.

A vehicle operating state estimation method based on improved extended Kalman filter includes using the improved extended Kalman filter algorithm for properly modeling to acquire operating state information such as longitudinal forward speed, yaw velocity, lateral speed, side slip angle and the like of a vehicle in a higher maneuvering operating state, wherein the information can be used for relevant control of vehicle active safety. The vehicle operating state estimation method based on improved extended Kalman filter has the advantages of high precision, low cost, high instantaneity and the like.

The invention discloses a light stream based vehicle motion state estimating method which is applicable to estimating motion of vehicles running of flat bituminous pavement at low speed in the road traffic environment. The light stream based vehicle motion state estimating method includes mounting a high-precision overlook monocular video camera at the center of a rear axle of a vehicle, and acquiring video camera parameters by means of calibration algorithm; preprocessing acquired image sequence by histogram equalization so as to highlight angular point characteristics of the bituminous pavement, and reducing adverse affection caused by pavement conditions and light variation; detecting the angular point characteristics of the pavement in real time by adopting efficient Harris angular point detection algorithm; performing angular point matching tracking of a front frame and a rear frame according to the Lucas-Kanade light stream algorithm, further optimizing matched angular points by RANSAC (random sample consensus) algorithm and acquiring more accurate light stream information; and finally, restructuring real-time motion parameters of the vehicle such as longitudinal velocity, transverse velocity and side slip angle under a vehicle carrier coordinate system, and accordingly, realizing high-precision vehicle ground motion state estimation.

The invention discloses a torque distribution control method for an electric-wheel automobile hub motor torque distribution system, and belongs to the field of an electric-wheel automobile. The electric-wheel automobile hub motor torque distribution system comprises parts as follows: a driver intention module, a hub motor, a stability controller, a torque distributor, a slip rate controller, a whole automobile module, a pavement information module and a whole automobile sensor module, wherein the stability controller comprises a fine adjustment mode and a stable adjustment mode, and the torque distributor divides whole automobile movement into a dynamic mode, an economical mode and a stable mode. According to the torque distribution control method, a plurality of controlled variables such as the slip rate, attachment coefficient, yaw velocity, side slip angle, hub motor rotating speed and the like are combined to control the automobile, so that stability and dynamic performance of the automobile at the low speed or high speed are guaranteed; and the automobile torque is distributed, so that automobile drive capacity, motor utilization efficiency and whole automobile stability when the automobile is driven normally or has a slipping phenomenon are improved.

A strategy is provided using feedback control algorithms to monitor and dynamically modify front and rear braking torque to maintain controllability in a vehicle that initially favors regenerative braking. Simple proportional-integral-derivative feedback controllers can be used. The controller can monitor wheel speed, lateral acceleration, yaw rate, and brake position to selectively activate non-regenerative braking independently for each individual wheel and regenerative braking in varying proportion based on at least one actual vehicle controllability value and at least one predetermined target value for controllability and optimization of energy recovery. Controllability factors can include predetermined longitudinal slip ratio, comparison of tire slip angle or yaw rate. For rear wheel drive configurations, the non-regenerative brakes can be applied to just one front axle wheel on the outside of a turn. For front wheel drive configurations, the non-regenerative brakes can be applied to just one rear axle wheel on the inside of a turn.

The invention discloses a key target identification method for an automobile cruising system. Based on the fuzzy control theory, a multi-target automobile lane changing fuzzy logic controller is designed, a dangerous lane changing automobile is prejudged, and effective identification of a straight lane key target is determined. The tilting motion influence of automobile bend running is considered, an extension Kalman filtering on-line real-time estimation of an automobile mass center side slip angle and a road curvature is achieved, the bend key target identification method is provided, a key target judgment basis is given, and effective identification of the bend key target is achieved.

The present invention is directed to a wheel grip factor estimation apparatus, which includes a steering factor detection unit for detecting at least one of steering factors including a steering torque and steering effort applied to a steering system extending from a steering wheel to a suspension of a vehicle, an aligning torque estimation unit for estimating an aligning torque produced on at least a wheel of the vehicle on the basis of the steering factor detected by the steering factor detection unit, and a vehicle state variable detection unit for detecting a state variable of the vehicle. The apparatus further includes a wheel factor estimation unit for estimating at least one of wheel factors including a side force and slip angle applied to the wheel on the basis of the vehicle state variable, and a grip factor estimation unit for estimating a grip factor of at least a tire of the wheel, in accordance with a relationship between the estimated alignment torque and the estimated wheel factor.

A vehicle motion control apparatus which is configured to control a motion of a vehicle comprising a plurality of apparatuses, each of which is configured to selectively control a slip angle or a yaw rate, is provided with: a behavior controlling device which is configured to perform behavior control in which a plurality of apparatuses are controlled such that a slip angle and a yaw rate are a set target slip angle and a target yaw rate, respectively; a turning state quantity specifying device which is configured to specify a turning state quantity of the vehicle; and a selecting device which is configured to select at least one of the slip angle and the yaw rate to be prioritized, on the basis of the specified turning state quantity in a case where the behavior control needs to be performed by one of the plurality of apparatuses. The behavior controlling device controls the one apparatus such that the selected one has the target value corresponding to the selected one, in the case where the behavior control needs to be performed by the one apparatus.

The invention relates to a multi-intelligent agent based unmanned electric car automatic overtaking system and method. The automatic overtaking system includes a vehicle-mounted sensor for acquiring front traffic information of an unmanned electric car. The automatic overtaking method includes: establishing a minimize safe distance model on the basis of feature information of a car and a surround environment thereof extracted by a vehicle-mounted sensing system and a V2X communication system; setting a sine function form as a base function of an automatic overtaking desired path, and dynamically planning an automatic overtaking desired track of the unmanned electric car in real time; adopting a self-adaption fuzzy slide mode control technique to solve the desired speed and the desired yaw velocity of overtaking of the unmanned electric car on the basis of a deviation between the desired overtaking path and an actual path; adopting a multi-intelligent agent genetic optimization algorithm to calculate out the required longitudinal and horizontal force of each wheel of the unmanned electric car; and establishing a mapping model from the longitudinal and horizontal forces of the wheels of the unmanned electric car to the desired slip angle and slip rate, and achieving execution control of the longitudinal and horizontal force of tires the unmanned electric car.

A method is provided for estimating vehicle velocity for a vehicle using a single-antenna global positioning system (GPS). An absolute speed and a course angle of the vehicle is measured using the single-antenna GPS. The yaw rates of the vehicle are measured independently of the GPS. An integrated yaw rate of the vehicle is calculated as a function of the measured yaw rates over a period of time. A yaw angle is determined as a function of a reference yaw angle and the integrated yaw rate. Aside slip angle is calculated as a function of the estimated yaw angle and the course angle provided by the GPS. The vehicle velocity is determined as a function of the absolute speed and the side slip angle. The vehicle velocity is provided to a vehicle dynamic control application.

The present invention provides a novel method for generating braking force in a wheel. In a vehicle having wheels, a wheel control device for controlling the wheels is provided with an actuator for performing an operation to vary a slip angle of the wheels, and a controller for controlling the actuator to increase the braking force of the wheels by increasing the slip angle absolute value of the wheels such that a lateral force is generated in the wheels relative to a ground contact surface of the wheels.

The invention provides a wheel longitudinal force regulation-based vehicle handling stability control method; the control method is applied to a vehicle with a mechanical steering system and without an active steering function. The control method comprises the following steps: (1) according to a signal input by a driver and a vehicle speed state, calculating a vehicle reference motion state by a vehicle reference model; (2) according to a vehicle motion state measured by a vehicle-mounted sensor, estimating to acquire a non-measured vehicle motion state as a vehicle real motion state; (3) based on sliding mode variable structure control, acquiring a target control force and a target control moment which are needed for the vehicle real motion state to track the reference motion state; (4) by regulating longitudinal force of the wheels, generating the needed target control force and target control moment. According to the control method, by regulating the longitudinal force of the wheels, nonlinear combined control on vehicle speed, yaw velocity and side slip angle can be realized, and the vehicle handling stability is improved.

The present invention is directed to a vehicle motion control apparatus, which includes a steering factor detection unit for detecting at least one of steering factors including a steering torque and steering effort applied to a steering system, an aligning torque estimation unit for estimating an aligning torque produced on at least a wheel of the vehicle on the basis of the steering factor, a vehicle state variable detection unit for detecting a state variable of the vehicle, a wheel factor estimation unit for estimating at least one of wheel factors including a side force and slip angle applied to the wheel on the basis of the vehicle state variable, and a grip factor estimation unit for estimating a grip factor of at least a tire of the wheel, in accordance with the estimated alignment torque and the estimated wheel factor. The apparatus further includes a first control unit for performing a closed loop control on the basis of the grip factor, and a second control unit for performing a closed loop control on the basis of a deviation between a detected actual vehicle behavior and a desired vehicle behavior set on the basis of the vehicle state variable.

Deformation of a tire is measured by a paired sensor 11 consisting of a 1st and 2nd strain gauges positioned on an inner liner of a tire with sensors mounted therein located equally spaced from and symmetrically with the center in an axial direction. Peak values of deformation speeds at the time of entering into the leading edge occurring at the time when the tire tread enters into the contact portion with a road surface are detected from the deformation wave from by differentiating with respect to time the wave form detected by the paired sensor and thus obtained peak values are designated as indication of deformation speed. Then, based on the ratio of thus obtained deformation wave indication and the Map 15M containing relation between thus obtained deformation speed ratio and time slip angle obtained beforehand, the slip angle of a vehicle under running condition is estimated, thereby enabling estimation of tire slip angle under vehicle running accurately.

The invention discloses a method for estimating a state during a running process of an automobile. The method comprises the following steps: analyzing a driving feature of the automobile and establishing a motion model of the automobile; introducing a non-integrity constraint for establishing a velocity error estimating equation; estimating errors along side direction and vertical direction during the running process of the automobile on the basis of a velocity and three attitude angles of the automobile; and establishing a slip angle estimating equation of the automobile. The stability of the automobile during the running process can be judged according to the velocity error estimation and slip angle estimation. According to the method, the on-line detection for a front-wheel steering angle of a four-wheel automobile can be realized by utilizing the motion model of the automobile. By adopting the method for estimating the state during the running process of the automobile, the real-time calculation and monitoring for state parameters of the automobile during the running process can be realized, for supplying data reference to safety running of the automobile.