652results about "Vehicle condition input parameters" patented technology

An AI-connected-electrified (ACE) heavy truck system equipped with an intelligent multi-mode hybrid (iMMH) powertrain system and a vehicle supervision control strategy based on machine learning (ML) or reinforcement learning (RL) paradigm are presented. This system ensures industry-leading power and braking performance of the ACE heavy truck while automatically optimizes both energy saving and emission reduction based on the vehicle's dynamic driving data and 3D electronic map information of roads for any transport event. In this application, the conventional analog electronic control (AEC) method is replaced by a novel digital pulse control (DPC) method on the instantaneous power function of the engine. The DPC method converts the complex surface working conditions of the AEC engine of the hybrid vehicles into simpler pre-defined working condition lines of the DPC engine. Consequently, the multi-variable nonlinear technical problem of simultaneously optimizing real driving environment (RDE) fuel consumption and pollutant emissions of the ACE heavy truck is simplified into two decoupled quasi-liner optimization problems, and ensures the reduction of on-vehicle computing resources for real-time AI inference computation and the improvement of the optimal performance, the convergent rate, and the robustness of the corresponding fuel-saving algorithm for the trained ML model or the learned RL model. Ultimately, the ACE truck achieves in the engineering sense the global minimum RDE fuel consumption and pollutant emissions meeting the standard consistently at high performance to cost ratio for any transport event and the RDE fuel consumption is decoupled from the vehicle configuration parameters and the human driver.

The application discloses a wind power blade transportation anti-overturning control method, which comprises the following steps: S1, determining a vehicle dangerous overturning line and inputting vehicle structure parameters; S2, reading sensor information in real time; S3, judging a vehicle running state; S4, calculating related parameters of a limit overturning state of the vehicle in a horizontal state, a low-speed running or parking state of the vehicle; S5, calculating related parameters of the limit overturning state of the vehicle in a high-speed running state; and S6, judging according to the values of five transportation danger coefficients respectively: when all the transportation danger coefficients η are less than or equal to 90%, the wind power blade transportation vehicle is in normal work, and the steps S2 to S6 are circularly performed; otherwise, a display issues a warning. The application also provides a calculation method of the transportation danger coefficient in the wind power blade transportation anti-overturning control. The application can help a driver to comprehensively understand a vehicle working condition, further improve the accuracy of a vehicle safety state judgment, and reduce the overturning phenomenon in the existing wind power blade transportation.

A method for determining a desired lateral acceleration of a vehicle is provided. The method may include determining a first raw lateral acceleration request based at least in part on a steering wheel angle of the vehicle. The method may also include determining a maximum allowable lateral acceleration based at least in part on the tire slip model. The method may also include determining a desired lateral acceleration based at least in part on the first raw lateral acceleration request and the maximum allowable lateral acceleration. The method may also include adjusting operation of the vehicle based at least in part on the desired lateral acceleration.

A model predictive lane centering (MPLC) control system with reference switching and disturbance rejection includes: an MPLC application having control logic that utilizes model predictive control (MPC) for selectively tracking static and dynamic references, adapts MPC weights and constraints for trajectory tracking when the system switches between static and dynamic references. A Kalman filter estimates a lateral force disturbance, a yaw moment disturbance acting upon a vehicle, and a measurement bias corrupting a measured yaw rate. The system detects anomalies in MPC reference trajectory and adjusts actuator constraints in response to detected anomalies. The system actively and continuously adjusts actuator outputs, causing the vehicle to track and follow a current lane center, and on receiving a lane change command, smoothly changes lanes using vehicle actuators to alter position and alter a vehicle trajectory to enter an adjacent lane before returning to tracking and following a center of the adjacent lane.

The invention relates to the field of computer vision, in particular to an intelligent parking system based on a computer vision algorithm, which is provided with a data acquisition module, a resource integration module, an anomaly analysis module, a parking matching module and a parking guide module, determines a vehicle running value and an actual parking effective value, calculates a parking permission characterization value, and displays the parking permission characterization value. Determining whether a parking position for a target vehicle exists in the parking area; determining a target parking area; dividing the target parking area into a plurality of sub-areas; analyzing data information corresponding to the target parking area; and parking guidance is carried out according to the judgment result of the preset condition, and intelligent parking is completed. According to the invention, parking guidance is carried out by determining the target parking area, analyzing the corresponding abnormal data and comparing with the parking related area of the target vehicle, so that the smoothness of the parking path and the parking efficiency are improved.

A dual-motor mixed-hybrid powertrain system, by performing pulse modulation control, i.e., series-hybrid intelligent start-stop control or parallel-hybrid intelligent power switching control, on the instantaneous power time-varying functions of an engine and a battery pack, can convert the surface working condition of an analog electric control engine into a simpler line working condition of a digital pulse control (DPC) engine, either a pre-determined high-state line working condition in the high-efficiency combustion area or a pre-determined non-combustion low-state line working condition with zero fuel consumption and zero pollutant emissions multiplexed in time. The traditional fixed one-to-one bidirectional mapping between an engine working condition and a vehicle working condition is converted into a dynamically adjustable many-to-many bidirectional mapping to achieve the full coverage of any overall vehicle working condition, achieving decoupling between a DPC engine working condition and the overall vehicle working condition and decoupling between software and hardware of a hybrid powertrain.

The invention provides a lateral movement sensing method and a vehicle, the method is applied to the technical field of vehicle control, and the method comprises the steps that a tire slip angle value at the current moment is obtained in response to a target calculation instruction of the vehicle; calculating an actual lateral force value at the current moment based on the tire slip angle value and the current wheel slip rate of the vehicle; and calculating the actual lateral motion acceleration of the vehicle according to the actual lateral force value, and evaluating the axle load transfer amount in the vehicle steering process according to the actual lateral motion acceleration. According to the method, the actual lateral force can be calculated in real time according to the tire slip angle and the wheel slip rate in various running states of the vehicle, then the actual lateral motion acceleration of the vehicle is accurately output, different working conditions can be adapted, and the real-time performance and accuracy of vehicle dynamics control are improved.

A lateral–vertical dynamics coordinated control method for a distributed drive electric vehicle, and a related device. The lateral–vertical dynamics coordinated control method for a distributed drive electric vehicle comprises the following steps: creating a fourteen-degree-of-freedom full vehicle model which considers unbalanced magnetic force in an in-wheel motor, so as to accurately represent a state response of a vehicle under different inputs; a three-dimensional piecewise affine tire model performing piecewise linearization of a lateral force of a tire under different side slip angles and vertical loads, so that nonlinear features of the tire can be described under extreme operating conditions; creating an active front-wheel steering controller on the basis of hybrid model predictive control, obtaining a reference center of mass side slip angle and a yaw rate by means of a bicycle model, and then calculating an additional steering angle of the vehicle, thereby ensuring vehicle stability; and designing a multi-constraint input and multi-constraint output active suspension controller based on dual-model predictive control by using roll stability and ride comfort, that is, a tire dynamic load, a vehicle body acceleration, and an in-wheel motor stator-rotor eccentricity, as suspension design control targets.

A traveling control apparatus for a vehicle that travels by transmitting force of a driving motor to tires is provided, including: a relaxation length calculation unit that calculates a relaxation length of the tires in a longitudinal direction as a moving distance required until a lateral force reaches a steady-state value when a slip angle is present in the tires; and a slip rate calculation unit that divides a deviation length of a deformation of the tires in the longitudinal direction, by the relaxation length calculated at the relaxation length calculation unit, thereby calculating a slip rate indicating a degree of slip between the tires and a road surface.

The invention discloses a path planning method and device for a parking task, a vehicle, a medium and a program product. The method comprises the steps that the planned length representing the steering capacity of a vehicle, the memory track of a vehicle parking task and the current position of the vehicle are obtained; determining a sampling end point based on the planned length and the memory trajectory; sampling on a memory track between the current position and the sampling end point to obtain a candidate point sequence; performing collision detection and course detection on each candidate point in the candidate point sequence to obtain a target sampling point passing the collision detection and the course detection; the target sampling point farthest from the current position of the vehicle in the target sampling points serves as a target point of the parking task; and performing path planning of the parking task based on the target point. According to the embodiment of the invention, the accuracy and reliability of target point selection can be improved.

Various embodiments of the present disclosure relate to a vehicle configured to execute a minimal risk maneuver, and a method for operating the vehicle. Disclosed is an autonomous driving vehicle, including: at least one sensor configured to sense surrounding environment of the vehicle to generate surrounding environment information; a processor configured to monitor state of the vehicle to generate vehicle state information and to control autonomous driving of the vehicle; and a controller configured to control operation of the vehicle according to the control of the processor, and the processor may be configured to sense whether a minimal risk maneuver is needed based on at least one among the surrounding environment information and the vehicle state information during autonomous driving of the vehicle; to determine a type of the minimal risk maneuver based on a normally operating function among functions specified for the minimal risk maneuver when the minimal risk maneuver is needed; and to control the vehicle to stop based on the determined type of the minimal risk maneuver.

A traveling control apparatus (10) for a vehicle (100) that travels by transmitting force of a driving motor (89, 90) to tires (111, 112, 121, 122) is provided, including: a relaxation length calculation unit (32) that calculates a relaxation length of the tires in a longitudinal direction as a moving distance required until a lateral force reaches a steady-state value when a slip angle is present in the tires; and a slip rate calculation unit (33) that divides a deviation length of a deformation of the tires in the longitudinal direction, by the relaxation length calculated at the relaxation length calculation unit, thereby calculating a slip rate indicating a degree of slip between the tires and a road surface.

A method for automated vehicle driving control in a platoon includes obtaining first operational parameters of a first vehicle, including at least a first measured braking performance of the first vehicle, obtaining second operational parameters of a second vehicle, including at least a first measured braking performance of the second vehicle, determining a platoon sequence according to the operational parameters by assigning whichever of the first vehicle and the second vehicle that has a lesser measured braking performance as a lead vehicle in the platoon sequence, and assigning the other of the first vehicle and the second vehicle as a follower vehicle in the platoon sequence, initiating a platoon sequence driving route, and controlling automated driving of the follower vehicle according to tracking of the lead vehicle, wherein the automated driving includes automated steering control, automated acceleration and automated braking based on tracked movement of the lead vehicle.

A vehicle for autonomous driving is capable of performing a minimum risk maneuver. The vehicle includes: at least one sensor, a processor and a controller, where the processor may detect whether a minimum risk maneuver (MRM) is required based on at least one of surrounding environment information and vehicle state information during autonomous driving of the vehicle, determine an MRM type based on a possibility of colliding with a neighboring vehicle when the MRM is required, and control to stop the vehicle based on the determined MRM type.

A road surface gradient estimation device includes an acquisition unit that acquires each of detection results of an acceleration detection unit that detects an acceleration in a front-rear direction of a vehicle, and a wheel speed detection unit, and acquires information regarding power for driving the vehicle, a derivation unit that derives a gradient of a road surface on which the vehicle is traveling as a first road surface gradient based on the acquired acceleration and wheel speed, and a correction unit that corrects the derived first road surface gradient based on the information regarding the power for driving the vehicle to derive a second road surface gradient.

A method of operating a vehicle includes receiving brake sensor data indicative of measured actuator outputs of a decentralized brake system's brake actuators. For each brake actuator, a vehicle controller calculates: a normalized corner output using the measured actuator output and a commanded target output for that brake actuator, and a weighted average using the normalized corner output of that brake actuator and a vehicle-calibrated weight value determined from the vehicle's current speed and steering angle. The controller calculates an actuator error percentage as an absolute value of a mathematical difference between the weighted averages of the brake actuators, and detects an actuator fault when the actuator error percentage exceeds a vehicle-calibrated fault deviation threshold determined from the vehicle's current speed and steering angle. Responsive to the error percentage exceeding the fault deviation threshold, the controller commands the brake system to execute a brake action to remediate the actuator fault.

Aspects of the present invention relate to a control system and method for controlling a state of charge of energy storage means of a hybrid electric vehicle, the control system comprising one or more electronic controllers, the one or more electronic controllers configured to: receive destination data; determine a route to be travelled by the vehicle, the route comprising one or more characteristics, in dependence on the received destination data; and control the state of charge of the energy storage means in dependence on the route to allow the vehicle to travel an end portion of the route in an electric-only mode.

Method, control means, vehicle, and computer program for implementing lane guidance in a vehicle The present invention relates to a method for implementing lane guidance of a vehicle (1), in which a control variable is determined via a lateral feedback control (7) based on a lateral spacing error describing the lateral deviation (4) of the vehicle (1) relative to a predetermined target trajectory (5), and the lateral position of the vehicle (1) is adjusted to the target trajectory (5) depending on the control variable, wherein at least one calibration value is additionally applied to the control variable, the calibration value being determined by at least one calibration function (12) at least partly depending on the time integral of the lateral spacing error.

A method (1000) for controlling a speed of a vehicle (1), in particular of a working machine such as a wheel loader (1), depending on a determined actual driving condition of the vehicle (1), the vehicle (1) comprising: a drive unit (2) that is coupled to at least one wheel (3) of the vehicle (1), wherein the drive unit (2) is configured for driving and braking the at least one wheel (3) of the vehicle (1), wherein the drive unit (2) is configured for braking by providing a motor braking torque, and a sensor unit (4) that is configured for detecting an actual speed value of the vehicle (1), and a brake system (5) that is coupled to at least one wheel (3) of the vehicle (1), wherein the brake system (5) is configured for braking the at least one wheel (3) of the vehicle (1), and a control unit (6) that is signalling coupled with the sensor unit (4), the drive unit (2), and the brake system (5), wherein the control unit (6) is configured for controlling the speed of the vehicle (1), the method (1000) comprising the steps: determining (1010) the actual speed value of the vehicle (1) provided by means of the sensor unit (4), and determining (1020) a maximum speed value and determining a critical speed value, wherein the critical speed value is larger than the maximum speed value, and determining (1030) the actual driving condition of the vehicle (1), wherein the driving condition is at least one of the following: an over speed driving condition if the determined actual speed value is larger than the determined maximum speed value and smaller than the determined critical speed value, an acceleration driving condition if the vehicle (1) is accelerated and the determined actual speed value is smaller than the determined maximum speed value, a regular driving condition if the vehicle (1) is not accelerated and the determined actual speed value is smaller than the determined maximum speed value, determining (1040) a target speed value of the vehicle (1) that is smaller than the determined maximum speed value, and wherein if the driving condition is determined as the over speed driving condition, the method (1000) comprising the steps of determining (1050) a speed braking signal value for actuating the friction braking unit depending on the determined target speed value, and providing (1060) the speed braking signal value to the brake system (5) for actuating the friction braking unit.

The invention relates to a method for assisting with driving a motor vehicle, comprising a step (E3) of generating a control response (Rep1) to be made with respect to a current situation, and a step (E4) of sending a command (K1) to an actuator in order to control the vehicle (10). In accordance with an item of quality information regarding the result of the command, the method further comprises a step (E5) of generating, by reinforcement learning, a new control response (Rep2), said new control response (Rep2) being optimised with respect to the current situation.

A method for operating a hybrid vehicle that operates in charge depletion and charge sustaining modes is described. In one example, a battery charge reserve amount is adjusted according to an altitude of a portion of a road that the hybrid vehicle may travel upon. The portion of the road is based on a radial distance from the hybrid vehicle's present geographical position.

The invention relates to a vehicle control unit arranged to: Obtain at least one data point from at least one vehicle sensor, the sensor being selected from among a tire pressure sensor, a window monitoring system sensor, a vehicle lift weight sensor, and an air conditioning system sensor; Evaluate whether additional fuel consumption is expected compared to the vehicle's current fuel consumption based on one or more data points from the vehicle sensors; and, if so, provide the user with information representative of said additional fuel consumption. Figure 1

This invention relates to a method for automatically guiding a vehicle (1) along a predetermined target trajectory, the target trajectory being characterized by geometric trajectory parameters. The method comprises at least the following steps: - knowing the actual deviation between the vehicle (1) and the target trajectory; - generating adjustment parameters based on the known actual deviation, such that the vehicle (1) approaches the target trajectory during automated drive control based on the generated adjustment parameters; - knowing whether there is an undesirable driving state at the current time point and / or future time point when the vehicle (1) approaches the target trajectory based on the generated adjustment parameters, wherein the undesirable driving state is known from the predetermined target trajectory based on the geometric trajectory parameters; and - when it is confirmed that there is an undesirable driving state at the current time point and / or future time point, - automatically driving the vehicle based on the generated stability parameters, and / or - adjusting the target trajectory.

A computer system (50), for assisting in coupling and uncoupling a semi-trailer (22) to a tractor vehicle (21), comprising processing circuitry (51) configured to use information provided by at least one sensor (40) to automatically check whether a plurality of elements (31, 32, 33, 34, 35) of the semi-trailer (22) and the tractor vehicle (21) are in a first safe position, in a second safe position or in a third position. The computer system (50) unlocks (S105, S205) a tractor vehicle parking brake (36) if all the elements (31, 32, 33, 34, 35) are in the first safe position or if all the elements are in the second safe position and locks (S109, S209) the tractor vehicle parking brake (36) if at least one of the elements (31, 32, 33, 34, 35) is in a different position than the others or in the third position.

An electric vehicle line variable control system and method for an electric vehicle may implement variable control of an EV line to lower the EV line by a specific level based on total traveling energy and required charging and discharging energy while the vehicle is traveling on a preset specific traveling route, so that the EV line is driven by the vehicle before the vehicle arrives at a destination using a stop mode. The battery SOC may be pre-managed as a target battery SOC that is higher than a reference SOC.

The invention relates to a method for determining the humidity of a soil over which rolls a tyre mounted on a vehicle, said tyre being provided with a sensor configured to acquire a measurement signal representative of the evolution of the curvature of the tyre as it rolls over the soil, comprising the following steps: - acquiring, by means of the sensor, a measurement signal representative of the evolution of the curvature of the tyre as it rolls, - determining, on the basis of the measurement signal, measurement data comprising: a) a first parameter (KSin) representative of a run-flat speed of the tyre when in contact with the soil, and b) a second parameter (KSout) representative of a rounding speed of the tyre when in contact with the soil, and - determining the humidity of the soil as a function of the first parameter (KSin) and of the second parameter (KSout).

The invention relates to a computer-implemented method for generating a virtual prototype with a vehicle on the basis of data from road measurements, comprising the following working steps: S1) providing a tire database comprising a plurality of tire data sets with Pacejka parameters; s2) providing a vehicle model, wherein the vehicle model is provided with a tire model which can be adjusted through the tire data set; s3) providing a tire data set for the tire model; s4) carrying out a measurement travel with a load event during which a measured value of a traction parameter of at least one of the tyres is determined; s5) simulating the load event with the vehicle model, at least one simulated value of the traction parameter of the tyre being output; s6) comparing the measured value of the traction parameter with the simulation value of the traction parameter; s7) adjusting the tire data set so as to adapt the simulation value of the traction parameter to the measured value of the traction parameter by changing the Pacejka parameter; wherein the working steps from S5 to S7 are repeated until a termination condition is reached; and then the value scale of the Pacejka parameter is output.

The present invention relates to a method (300) for starting an internal combustion engine (101) in an electric hybrid vehicle (100). The method comprises, for at least one first vehicle driving condition, when the internal combustion engine (101) is disconnected from the at least one first drive wheel (111a, 111b), and is to be started when the vehicle (100) is in motion: accelerating (320) the internal combustion engine (101) using drive wheel torque by partially closing the clutch (103) to connect the internal combustion engine (101) to the at least one first drive wheel (111a, 111b), applying (330) a vehicle propelling torque by the electric machine (110) while accelerating the internal combustion engine (101), so as to at least partly compensate for drive wheel torque being used to accelerate the internal combustion engine (101), and commencing (340) fuel injection to start the internal combustion engine (101). The invention also relates to a control arrangement, a computer program, a computer-readable medium and a vehicle comprising a control arrangement.

A fire fighting vehicle includes a powertrain, an accessory drive, and a controller. The powertrain includes an engine, an energy storage device, and an electromechanical transmission (i) electrically coupled to the energy storage device and (ii) selectively mechanically coupled to the engine. The electromechanical transmission is configured to (a) selectively drive a front axle and / or a rear axle and (b) selectively generate energy for storage in the energy storage device as stored energy. The accessory drive is positioned to receive a mechanical input from the engine and the electromechanical transmission. The controller is configured to selectively operate the powertrain in (i) a standby mode by operating the electromechanical transmission using the stored energy to drive the accessory drive with the engine off and (ii) a rollout mode by operating the electromechanical transmission using the stored energy to drive the the front axle and / or the rear axle with the engine off.