641 results about "Vehicle acceleration" patented technology

The invention relates to the field of vehicle braking fault detection, in particular to a real-time fault detection method for a vehicle electronic braking system, which comprises the following steps of: acquiring vehicle driving state data through a vehicle-mounted sensor network and an electronic control unit, calculating filtered residual data of a target wheel speed sensor, and calculating the filtered residual data of the target wheel speed sensor; establishing calibration reference parameters of the health state; performing conjoint analysis on the acceleration data and the residual fluctuation data of the vehicle to obtain a dynamic response adaptive adjustment factor of the vehicle; obtaining a tiny drift confirmation factor of the vehicle through the candidate residual error in the low dynamic interference state of the vehicle; continuous fault judgment is performed by combining the dynamic response adjustment factor and the tiny drift confirmation factor of the vehicle, and the fault judgment result of the wheel speed sensor is obtained, so that the accuracy and sensitivity of fault detection when tiny systematic deviation occurs to the wheel speed sensor are improved.

The invention discloses a hybrid electric vehicle predictive energy management system based on multi-layer cooperative control, and aims to improve the vehicle performance and energy efficiency. According to the method, a hierarchical cooperative control architecture is adopted, and the reinforcement learning, vehicle speed multi-step prediction and model prediction control technologies are combined, so that joint optimization control over vehicle acceleration and power distribution is achieved. The system obtains the vehicle running state and the surrounding environment information in real time through the state sensing module, and determines the expected acceleration by using a strategy network trained by a PPO algorithm. In addition, the future vehicle speed is predicted in combination with an XGBoost multi-step regression model, the optimization module is designed through an MPC strategy, oil consumption, the battery state and driving smoothness are comprehensively considered, and therefore efficient management of the power system is achieved. According to the scheme, the obvious energy-saving advantage is achieved, the driving smoothness and comfort are improved, the good self-adaptive capacity and a real-time feedback mechanism are achieved, and the method is suitable for the complex urban road traffic environment.

The invention relates to the technical field of electric vehicle control, in particular to an AI-based electric vehicle intelligent starting and acceleration control method and system. The method comprises the following steps: acquiring a driving log of a vehicle owner, performing intelligent vehicle optimization after starting, and constructing an intelligent starting mode selection strategy; physiological state data of a driver are obtained, state change evolution analysis is carried out, and a personalized driving portrait is constructed; holographic state sensing and vehicle virtual simulation are carried out, and a vehicle synchronous digital simulation model is constructed; radar feedback sensing information and a real-time monitoring image in front of a vehicle are collected, traffic situation prediction and vehicle scene prediction and perception are carried out, and a vehicle scene prediction and perception model is constructed. According to the method, the driving starting mode of the vehicle is intelligently selected, vehicle owner requirements and environment available power constraints are matched, and vehicle acceleration efficiency maximization and safety optimization are achieved.

A vehicle acceleration control method, includes: obtaining a change rate of an accelerator pedal opening degree of an accelerator pedal and a remaining energy value of a vehicle in a racetrack mode; determining a target torque compensation value based on the change rate of the accelerator pedal opening degree and the remaining energy value of the vehicle; and controlling the vehicle to accelerate based on a sum of the target torque compensation value and a maximum output torque value.

The embodiment of the invention provides a trapped vehicle escape state recognition control method, device and system, and the method comprises the steps: obtaining the wheel speed, wheel acceleration, vehicle speed and vehicle acceleration of a target vehicle; determining a wheel slip rate based on the wheel speed and the vehicle speed; determining the wheel slip number based on the wheel slip rate; based on the vehicle speed, the wheel slip rate, the wheel slip number, the vehicle acceleration and the wheel acceleration, the current state of the target vehicle is determined; the target vehicle speed of the target vehicle is corrected based on the current state, and the target vehicle speed is used for guiding the target vehicle to run. The technical problems that in the prior art, when the vehicle speed is low, the vehicle trapping state of the vehicle cannot be accurately judged, and the vehicle cannot be controlled to be out of trap according to the accurate vehicle trapping state are solved.

A control system for a vehicle is provided, the control system comprising one or more controllers, the control system configured to receive an acceleration or deceleration demand signal from an automatic cruise control system, and request modification of one or more parameters of the vehicle suspension system in response to the received acceleration or deceleration demand signal. In this way, the vehicle suspension system may be modified in preparation for an acceleration or deceleration of the vehicle, to inhibit or at least reduce the occupants of the vehicle experiencing an undesirable pitching movement of the vehicle during the course of the change in speed of the vehicle.

The invention relates to a vehicle control method and device, a vehicle and a medium, and relates to the technical field of control. The control method comprises the steps that according to the first pedal opening degree of an accelerator pedal of the vehicle, the acceleration intention of a driver of the vehicle is determined; according to the acceleration intention and the running speed of the vehicle corresponding to the first pedal opening degree, a correction coefficient corresponding to the first pedal opening degree is determined; determining a second pedal opening degree according to the correction coefficient and the first pedal opening degree; and performing acceleration control on the vehicle according to the second pedal opening degree. According to the technical scheme, the energy utilization rate of the vehicle can be increased.

The invention relates to the technical field of automatic driving, and particularly discloses a low-delay moving target detection method and system for navigation, and the method comprises the steps: collecting an event flow through a vehicle-mounted event camera; adjusting the time window length of the event flow in real time according to the vehicle speed, the vehicle acceleration and the event density gradient to obtain an event image; inputting the event image into a pulse neural network to obtain an output feature map; detecting the feature map through a feature pyramid network and a detection head to obtain a motion trail flow of the target; and performing nonlinear model predictive control according to the motion trail flow to obtain an optimized motion trail flow of the target.

The invention discloses an automobile driving state blind area monitoring method and a rearview mirror, and relates to the technical field of blind area monitoring. Comprising the following steps of information collection, specifically, sensors and cameras are installed on wheels of an automobile, a steering wheel steering column, an automobile chassis and a steering system respectively, driving state data of the automobile speed, the steering wheel angle, the automobile acceleration and the steering angle and image data around the automobile are collected in real time, and real-time automobile information data are obtained; according to the system, driving state data such as the vehicle speed, the steering wheel angle, the vehicle acceleration and the steering angle are combined, the blind area around the vehicle is monitored in real time through the sensor and the camera, and when the vehicle steers, the blind area monitoring range is adjusted in real time to adapt to the driving direction change; the rearview mirror can display blind area images in real time, the blind area alertness of a driver can be greatly improved, and the traffic accident risk caused by the blind area is effectively reduced.

Aspects of the disclosure relate to thermal management aspects of a battery pack. A casted front member of a battery pack enclosure may facilitate cooling of a high voltage distribution box (HVDB) within a cavity of the casted front member. Cooling of other electrical components, such as a busbar can also be provided. Cooling of the HVDB and / or other electrical components external to the battery modules and / or battery cells in a battery pack can facilitate fast charging, vehicle acceleration, component reliability, and / or other advantages.

A method includes receiving an indication regarding a deceleration event for a vehicle, remapping a response of a prime mover of the vehicle from following a first response curve to following a deceleration response curve in response to (i) the deceleration event and (ii) a speed of the vehicle being greater than a speed threshold, and activating an output of the prime mover to accelerate the vehicle at a relatively lesser amount of depression of an accelerator from a non-depressed state of the accelerator than prior to the deceleration event in response to the accelerator being engaged by an operator following the deceleration event.

The invention provides an intelligent vehicle lane change decision-making method based on a master-slave game in a mixed driving scene, which comprehensively considers the human driver style and the dynamic trajectory influence of surrounding vehicles in various typical lane change scenes, and establishes a more comprehensive multi-vehicle game framework based on the master-slave game. Comprehensive game cost and revenue functions are respectively established for intelligent vehicles and human-driven vehicles on adjacent lanes, and an optimal intelligent vehicle acceleration sequence and lane changing time are iteratively calculated through a double-layer optimization model structure. The accurate planning of the lane changing track of the intelligent vehicle can be realized on the premise of considering multiple aspects such as safety, comfort and traffic efficiency.

The present invention relates to the technical field of autonomous driving, and disclosed are a vehicle acceleration anomaly processing method and apparatus, a storage medium, and a vehicle. The method comprises: acquiring a real-time acceleration command signal and an actual acceleration signal of a vehicle, wherein the acceleration command signal is used for representing a calculated desired acceleration to be achieved of the vehicle, and the actual acceleration signal is used for representing a measured actual achieved acceleration of the vehicle; on the basis of the acceleration command signal and the actual acceleration signal, performing acceleration anomaly detection on the vehicle to obtain a detection result; and in response to the detection result that an acceleration anomaly is present in the vehicle, adjusting an autonomous driving acceleration behavior of the vehicle on the basis of a target processing strategy, wherein the target processing strategy is determined on the basis of an anomaly category of the acceleration anomaly. The present invention solves the technical problem of low autonomous driving safety caused by high difficulty and low precision of the detection of acceleration anomalies in existing autonomous driving functions.

The invention relates to the technical field of AMT gearbox control, in particular to an AMT gearbox control method, system and equipment in a braking state and a medium, and the method comprises the steps that when a vehicle is in a braking deceleration state, the stepping duration of a brake pedal, the actual vehicle speed, the actual acceleration of the vehicle and the rotating speed of an engine are obtained; whether the braking intention of the driver is emergency braking or stable braking is judged based on the stepping duration of the brake pedal and the actual acceleration of the vehicle; and based on the braking intention, the gear of the AMT gearbox and the separation state of a clutch are controlled till braking is finished. Wherein the current gear is maintained during emergency braking, and a clutch is controlled to be separated according to an engine rotating speed threshold value; during stable braking, after the rotating speed of the engine meets the condition, whether downshift is conducted or not is judged according to the actual vehicle speed, and a clutch is controlled to be separated. The brake intention of a driver can be accurately recognized, differential control is executed, and therefore the brake efficiency is effectively improved, engine flameout is prevented, and the driving smoothness is improved.

The invention discloses an abrupt slope slow descent system based on energy recovery, and particularly relates to the technical field of vehicle control, and the system comprises a slope estimation module which receives a vehicle speed signal and a vehicle acceleration signal, and estimates the current slope of a vehicle through the vehicle speed signal and the vehicle acceleration signal; the abrupt slope slow descent activation judgment module is used for receiving a slope signal, a vehicle gear signal, a brake pedal signal, an accelerator pedal signal, a driving direction signal and a driving mode signal; when the vehicle is on the slope, a brake pedal and an accelerator pedal are not stepped on, and the vehicle speed is within a vehicle speed threshold interval, the abrupt slope slow descent function is activated, and otherwise, the abrupt slope slow descent function exits; the target vehicle speed calculation module identifies the intention of the driver and gives a target vehicle speed; and the electromechanical braking force distribution module introduces feedforward control through a gradient signal firstly, then gives target braking force by superposing closed-loop control of a target vehicle speed, and then distributes the braking force to electric braking and mechanical braking to realize energy recovery and caliper braking respectively.

A multi-vehicle control system (MVCS) for control of a multi-vehicle system having independently powered and steered lead and trailer vehicles connected by a slidable length sensing tow bar system. The MVCS includes a controller configured to receive throttle, brake, and steering signals from the lead vehicle, receive signals from the tow bar system indicating an extension length of the tow bar system, a front angle deviation of the lead vehicle, and a rear angle deviation of the trailer vehicle. The controller is further configured to determine, based on the received signals, a trailer vehicle acceleration / deceleration output and a trailer vehicle steering output, determine a driving scenario of the multi-vehicle system, and operate the multi-vehicle system based on the determined driving scenario and the determined trailer vehicle acceleration / deceleration output and trailer vehicle steering output.

The present invention discloses a pedal jamming monitoring method for identifying braking intention based on multi-source data fusion, belonging to the field of automotive braking. S1: Synchronously collect the pressure applied to the brake pedal, the displacement of the brake pedal under the applied pressure, the displacement of the accelerator pedal, and the vehicle acceleration, and obtain the current driving environment information; S2: Calculate the pedal position change rate, the pedal force change rate, the throttle opening change rate, and the relative distance ratio between the current vehicle and the vehicle in front; S3: Use a random forest to generate a preliminary identification intention; S4: Generate a final identification intention; S5: Determine whether there is jamming. By adopting the above-mentioned pedal jamming monitoring method for identifying braking intention based on multi-source data fusion, through fusing multi-source data such as brake pedal displacement, pressure, throttle state, and environmental parameters, and combining mechanisms such as dual-model decision-making, dynamic threshold adjustment, and multi-rule weighted judgment, the accuracy, real-time performance, and environmental adaptability of brake pedal jamming monitoring are significantly improved.

The invention belongs to the field of intelligent traffic, and particularly relates to a construction area traffic flow guiding and speed cooperative control system which realizes accurate traffic flow control through cooperative operation of an area sensing module, a distributed guiding module, a communication module and an emergency response module. The area sensing module is based on three-dimensional modeling and digital twinning technologies, fuses real-time traffic flow, vehicle states and environment data, and constructs a three-dimensional simulation space of a target area; the distributed guide module establishes a drainage control model by using a distributed reinforcement learning algorithm, dynamically optimizes a sub-region congestion control strategy in combination with a vehicle-road-cloud three-level communication node, and adjusts the acceleration and speed of a vehicle in real time; and the emergency response module rapidly generates an emergency instruction through an anomaly analysis algorithm and a strategy library and feeds back the emergency instruction to the guide model to solve an emergency abnormal event, and the application integrates multi-source data real-time sensing, distributed decision optimization and a multi-stage communication architecture, and realizes dynamic traffic flow distribution and intelligent traffic control in a construction area.

The invention provides an in-vehicle acoustic enhancement method and device fusing determinacy-randomness hybrid modeling, and the method comprises the steps: collecting a fitted vehicle acceleration sound sample, extracting audio data, carrying out the analysis, constructing a determinacy component synthesis algorithm, and associating with a vehicle working condition; the method comprises the following steps: constructing a multi-physics-field coupled random noise generation module, wherein the multi-physics-field coupled random noise generation module comprises an aerodynamic noise module for simulating air inlet turbulence, a low-frequency pulse module for representing mechanical shock, a detonation module for simulating combustion uncertainty and a nonlinear distortion module for enhancing exhaust roughness and generating high-order harmonics; each random noise generation module is matched with the deterministic component, and mixing of the deterministic component and the random component is realized through weight adjustment; details are enhanced through dynamic compression, and target sound waves are generated; through collaborative optimization of determinacy-randomness components, the naturalness and brand identification degree of synthetic sound waves are improved, the vehicle working condition and driving information can be converted into perceptible sound effect characteristics, and the problem of information perception simplification in the electric vehicle driving process is solved.

A system for detecting and correcting wheelspin in a vehicle powered by a motor includes drive wheels driven by the motor and a motor controller in communication with the motor. In one embodiment, a vehicle acceleration from an inertial measurement unit (IMU) is compared to an estimated vehicle acceleration determined from an acceleration of the motor's rotor. If the estimated vehicle acceleration is greater than the IMU acceleration the motor controller adjusts the motor to correct the wheelspin. In a second embodiment, the vehicle acceleration is determined from a GPS receiver. In further embodiments, the vehicle acceleration is determined from other motor parameters, including voltage, current, and torque. In various embodiments, the drive motor is an electric motor, an internal combustion engine, or other prime mover device or mechanism.

The invention relates to a verification method and device for the explosion safety margin of an automobile safety airbag and a storage medium, and the method comprises the steps: setting the braking force of a braking mechanism of an acceleration type trolley according to a weighted acceleration curve, and simulating the forward impact when an automobile is collided according to the braking force of the braking mechanism; monitoring an explosion signal of a safety air bag controller installed on the acceleration type trolley; and comparing the difference between the air bag ignition time actually collected by the current clamp in different weighted states and the target air bag ignition time, and determining the safety margin of the safety air bag controller meeting the preset maximum calibration condition according to the actual comparison data. According to the embodiment of the invention, the ACU can be installed on the acceleration type trolley to simulate the whole process of vehicle collision, and the simulation of the acceleration of the whole vehicle in a low-speed collision accident of the vehicle is realized, so that the airbag unfolding condition and the safety margin of the ACU in an actual accident are verified, the vehicle collision test requirements are reduced, and the vehicle collision test number is reduced.

To provide a support apparatus, a support method, and a program capable of securing prompt response to an accident.SOLUTION: A support apparatus is configured to: acquire acceleration data indicating acceleration of a vehicle and contract data corresponding to the vehicle; determine whether an impact corresponds to a serious accident in a plurality of accident types, based on the acceleration data and the contract data; transmits, when the impact is determined to be an impact corresponding to a serious accident, an instant payment notification which is a notification about insurance payout in a shorter period than the case where the impact is not a serious accident. Accordingly, a quick response to an accident can be secured.SELECTED DRAWING: Figure 10

The invention relates to the technical field of electric quantity consumption prediction, and discloses a new energy automobile electric quantity consumption prediction analysis method based on intelligent network connection, which is used for solving the problem of inaccurate acceleration acquisition during point electric quantity consumption, and comprises the following steps: acquiring a trigger frequency intervened by a stability control system in a detection time period, performing first influence judgment according to the trigger frequency, if the judgment result is that the acceleration of the vehicle is influenced by the intervention of the stability control system, acquiring intervention trigger parameters in each unit time in the detection time period, performing evaluation to obtain a trigger strength index, performing second influence judgment according to the trigger strength index, and if the judgment result is that the acceleration of the vehicle is influenced by the intervention of the stability control system, performing second influence judgment according to the judgment result. The vehicle acceleration is influenced by intervention of the stability control system, the acceleration in the initial operation data is corrected, the actual acceleration is obtained, the accuracy of electric quantity consumption prediction is effectively improved, and the user experience feeling is improved.

A vehicle includes a suspension system having a damping system that includes a plurality of dampers and a plurality of damper valves. The vehicle further includes one or more processors configured to determine energy content of an acceleration signal indicative of acceleration of the vehicle. The one or more processors are further configured to dynamically tune a cutoff frequency of a high-pass filter based on the energy content of the acceleration signal. The one or more processors are configured to filter, via the high-pass filter, a velocity signal derived from the acceleration signal to output a filtered velocity signal. The one or more processors are configured to control operation of the damping system based on the filtered velocity signal.

The invention belongs to the technical field of transportation container equipment, and particularly relates to an unmanned underwater vehicle transportation device which comprises a tool base used for storing an unmanned underwater vehicle. The tool base comprises a bottom fixing frame, a supporting frame, a stand column, a top hanging frame and a hanging tool seat locking frame, and further comprises a stress relieving mechanism. By arranging the stress relieving mechanism, in the vehicle acceleration or deceleration motion process or the vehicle uniform-speed uphill and downhill process, the vehicle can be lifted up and down through lifting motion of jacks located at the two ends of the bottom fixing frame; the inclination angle and the inclination direction of the jacking frame and the unmanned underwater vehicle are adjusted, then the characteristic that the inclination angle decomposes inertia force and gravity is utilized, stress gathered on the lifting tool seat and the lifting tool seat locking frame by the inertia force or the gravity is effectively reduced, and the unmanned underwater vehicle is limited and borne through the cooperation of the tool base. Therefore, the transportation stability of the unmanned underwater vehicle is effectively improved.

The article is an electric motor used in mobility applications (e.g., electric vehicles). The article is connected to and drives the wheels of the vehicle. The article is configured to convert generated electrical energy for accelerating or decelerating the vehicle into mechanical energy for driving the wheels of the vehicle.

The invention discloses a vehicle turning control method and device and a distributed driving vehicle, and relates to the technical field of vehicles. The method comprises the steps that under the condition that the current working condition of a vehicle is a curve acceleration working condition, the total yawing moment is determined based on target driving force corresponding to all wheels in the vehicle; on the basis of the total yaw moment and an aggressive degree coefficient corresponding to the current driving mode, compensation yaw moment is determined; the aggressive degree coefficient is related to the average transverse acceleration of the vehicle within the preset duration closest to the current moment; determining a target rear wheel steering angle corresponding to the compensated yaw moment; an angle of a rear wheel in the vehicle is adjusted based on the target rear wheel steering angle to accelerate the vehicle through the curve. By adopting the method, the efficiency of the vehicle passing through the curve and the driving safety can be improved under the condition that the vehicle runs on the curve.

The invention relates to the technical field of data control, and particularly discloses a multi-motor coordination control method and system based on dynamic load compensation, and the method comprises the steps: obtaining the posture data and driving state data of a whole vehicle; estimating a current road slope angle; calculating actual vertical loads of front and rear wheels; a variable weight harmonic decomposition mechanism is adopted to execute an anti-interference and torque proportion cooperative decomposition task; and executing a multi-motor coordination control task by adopting a model prediction control algorithm. In the prior art, motor torque distribution is carried out only based on static vehicle parameters or whole vehicle homogeneous hypothesis, and especially under dynamic working conditions such as vehicle acceleration climbing, low-speed heavy load or dramatic change of load migration, accurate torque coordination and load sensing control optimization between motors cannot be realized. Due to the fact that the dynamic load compensation mechanism is constructed and coordinated control of the model predictive control algorithm is combined, the response performance and coordinated control precision of the vehicle power system are remarkably improved.

A device positionable in a passenger compartment of a vehicle can include a processor, an accelerometer, and a wireless transmitter. The processor can receive, while in a hibernation mode, an interrupt signal from the accelerometer based on the accelerometer detecting an acceleration of the vehicle that exceeds a predefined acceleration threshold. In response to receiving the interrupt signal from the accelerometer, the processor can switch from the hibernation mode to a sleep mode. While in the sleep mode, the processor can detect a trip start event based on one or more accelerometer values from the accelerometer. In response to detecting the trip start event, the processor can then switch from the sleep mode to an active mode. While in the active mode, the processor can receive additional accelerometer values from the accelerometer and store them for subsequent transmission to a remote server system using the wireless transmitter.

The invention relates to the field of vehicle navigation, and particularly discloses a vehicle navigation method and system based on inertial navigation, and the method comprises the steps: collecting vehicle acceleration and angular velocity data through an inertial measurement unit, constructing a hypergraph structure, integrating road, environment and vehicle state nodes, mining a potential relationship of multi-source heterogeneous data by using a hypergraph neural network algorithm, and obtaining a vehicle navigation result; and designing a data resolving rule to realize data fusion analysis. On the basis, the real-time position of the vehicle is calculated, an optimal path considering dynamic factors is planned, and visual navigation information is output. The system comprises an inertial data acquisition unit, a hypergraph construction and processing unit, a multi-source heterogeneous data calculation unit and the like, all the units work cooperatively, and the navigation performance is improved through model collaborative optimization. The method gets rid of dependence on satellite signals, solves the problem of positioning in a complex environment, effectively utilizes multi-source data, and realizes accurate and dynamic vehicle navigation.