3003 results about "Driving mode" patented technology

The invention discloses a multi-mode energy recovery optimization control system of a hybrid electric vehicle, and relates to the technical field of energy recovery control. The state sensing module is integrated with a sensor to collect vehicle speed, acceleration, battery state and road condition signals, and data accuracy is ensured through Kalman filtering fusion; the driving mode recognition module is used for recognizing modes such as urban congestion and high-speed cruise through an algorithm based on driving behaviors and road conditions; the energy recovery strategy decision module is used for dynamically adjusting recovery priorities and parameters according to different modes, and balancing efficiency and smoothness; the power distribution execution module converts and stores energy through cooperative control of double clutches and a gearbox, and is linked with an ABS (Anti-lock Brake System) to guarantee safety; and the feedback module is optimized in real time, battery and motor states are monitored, strategies are dynamically corrected, and efficiency and component protection are both considered. The energy recovery efficiency is improved, the driving smoothness and the braking safety are improved, the system adapts to multiple scenes, the service life of the battery is prolonged, and the performance of the hybrid electric vehicle is comprehensively improved.

The invention provides a gear switching method, a vehicle and a storage medium, the method is applied to the technical field of hybrid power control, and the method comprises the steps that in the process that the vehicle runs based on a direct drive mode, if it is determined that the vehicle needs to switch gears, the whole vehicle driving power corresponding to the direct drive mode and the discharging power of a power battery are determined; based on the whole vehicle driving power, the discharging power and the gear change state of the vehicle, a target torque reduction gradient is determined; based on the target torque reduction gradient, the actual torque of the engine is controlled to be reduced to the target torque; and under the condition that the actual torque of the engine is equal to the target torque, the clutch is controlled to be in an open state, so that the vehicle is shifted under the condition that the clutch is in the open state. The method can ensure that the power is not interrupted in the vehicle gear shifting process, the vehicle stability is improved, and the user driving experience is improved.

The invention provides a wind power plant unit state monitoring and fault early warning system and method based on deep learning, and belongs to the field of wind power generation and artificial intelligence. According to the system, a cloud edge collaborative architecture is adopted, an edge computing terminal operates a data-driven space-time prediction model and a physical digital twinborn model in parallel, and abnormity is preliminarily screened by calculating a double-track residual error and comparing the double-track residual error with a dynamic early warning threshold value. And when an exception occurs, the cloud platform receives multi-modal data including a sensor, a model state and an operation and maintenance text, performs deep root cause analysis by using a diagnosis model fused with a wind power fault knowledge graph, and generates an interpretable diagnosis report. According to the method, deep fusion of data and a physical model is realized, and the accuracy of fault monitoring, the interpretability of diagnosis and the intelligent level of operation and maintenance decision are remarkably improved through a data-physical double-track driving mode.

The invention discloses a vehicle operation control system, method and equipment, a medium and a product. The system comprises an operation state determination subsystem used for determining predicted operation situation information associated with a vehicle; the operation constraint subsystem is used for determining vehicle operation constraint parameters based on the predicted operation situation information and determining a to-be-driven mode of the vehicle; the motion control subsystem is used for determining an actuator reference instruction based on the predicted operation situation information, the to-be-driven mode, the vehicle operation constraint parameters and the to-be-driven track; the control distribution subsystem is used for determining an actuator distribution instruction of a plurality of actuators in the vehicle based on the actuator reference instruction and the predicted operation situation information; and the coordination control subsystem is used for determining target actuator instructions of the plurality of actuators based on the to-be-driven mode and the actuator distribution instruction, and controlling the actuators to operate based on the target actuator instructions. The control consistency, the response real-time performance, the operation safety and the comfort of the whole vehicle in a complex dynamic scene are improved.

The present application provides a fault identification method and apparatus for an autonomous driving system. The method comprises: acquiring travelling-related data of an ego vehicle (at least including ego vehicle travelling data and target obstacle motion data); respectively performing feature extraction on the travelling-related data of the ego vehicle on the basis of a plurality of feature extraction networks to obtain feature vectors of the ego vehicle from a plurality of viewing angles; fusing the feature vectors from the plurality of viewing angles to obtain a global driving scenario feature vector of the ego vehicle; and on the basis of the global driving scenario feature vector, determining a target driving scenario where the ego vehicle is located in a current driving mode and whether a fault occurs to an autonomous driving system in the target driving scenario. In the present application, dynamic change information of an ego vehicle and a surrounding environment of the ego vehicle is captured from a plurality of viewing angles, the information from the plurality of viewing angles is adaptively fused to obtain comprehensive representations of driving scenarios, and a target driving scenario where the ego vehicle is currently located and whether a fault occurs to an autonomous driving system in the target driving scenario are identified on the basis of the comprehensive representations, thereby improving the accuracy of fault identification results of the autonomous driving system.

The invention provides an off-line test method and an off-line test device for a vehicle steering system, and the method comprises the steps: controlling a vehicle to run according to a preset test track through activating an automatic driving mode of the vehicle; in the running process of the vehicle, running state data of the vehicle are collected in real time; and comparing the operation state data with a preset quality standard, and generating an offline test result of the vehicle steering system based on a comparison result. In the mode, the vehicle is controlled to run along the preset test track by adopting automatic driving, so that the test control precision of the vehicle steering system can be improved, and the accuracy and consistency of off-line test are further improved.

The invention provides a vehicle driving state estimation method and system in a centralized driving mode, and relates to the technical field of electric automobiles, and the method comprises the following steps: determining wheel dynamic parameters based on sensor detection information and a seven-degree-of-freedom dynamic model related to wheels, and combining a preset Dugoff tire model to obtain initial tire force parameters; a vehicle-mounted infrared camera is used for obtaining road surface image information, the road surface image information is analyzed through a deep convolutional neural network based on semantic segmentation and a vehicle dynamics inversion method, an adaptive fusion mechanism is introduced for adjustment, and a target road surface adhesion coefficient is determined; correcting the initial tire force parameter by using the target road adhesion coefficient to obtain a target tire force parameter; inputting the current sensor detection information and the target tire force parameter into a self-adaptive unscented Kalman filter to obtain vehicle driving state information; the vehicle driving state information comprises the longitudinal speed, the transverse speed, the yaw velocity and the side slip angle of each tire.

Apparatus, systems, and methods are contemplated for electric powered vertical takeoff and landing (eVTOL) aircraft. Such are craft are engineered to carry safely carry at least 500 pounds (approx. 227 kg) using a few (e.g., 2-4) rotors, generally variable speed rigid (non-articulated) rotors. It is contemplated that one or more rotors generate a significant amount of lift (e.g., 70%) during rotorborne flight (e.g., vertical takeoff, hover, etc), and tilt to provide forward propulsion during wingborne flight. The rotors preferably employ individual blade control, and are battery powered. The vehicle preferably flies in an autopilot or pilotless mode and has a relatively small (e.g., less than 45′ diameter) footprint.

The invention discloses a fuel cell hybrid electric vehicle power distribution method based on heuristic action planning deep reinforcement learning. The method comprises the following steps: establishing a power distribution system model of a fuel cell hybrid electric vehicle equipped with a lithium battery and a super capacitor; a power layered structure is provided, a deep reinforcement learning model of the fuel cell hybrid electric vehicle is designed, a probability transfer matrix of required power is constructed, and model training is performed in a data driving mode; designing a reward function by adopting an equivalent consumption minimum strategy, and guiding optimization of an energy management strategy by fuel economy; the motion space of deep reinforcement learning is improved by adopting heuristic planning, and smooth output of the fuel cell is kept on the premise of reducing equivalent hydrogen consumption. According to the method, power distribution of the three-energy-source fuel cell hybrid electric vehicle can be achieved in a complex and random driving environment, hydrogen consumption is reduced, dynamic adaptability to different driving conditions is improved, and meanwhile the method has the potential of real-time application.

A processor of a device for providing a route according to an embodiment of the present invention may, on the basis of entering a first lane-maintaining driving mode, cause a vehicle to drive so as not to deviate from a first lane, and on the basis of a preset condition being satisfied, may enter a second lane-maintaining driving mode in which the vehicle is caused to drive in the first lane and a second lane adjacent to the first lane.

This document describes, among other things, a vehicle power system that includes a traction battery, a six-phase inverter divided into two groups of six switches, a six-phase motor, and a pair of switches. In drive mode, the switches configure the inverter to connect the traction battery and the motor. In plug-in mode, the system reconfigures so that one group of switches connects an AC source to the motor, while the other group connects the motor to the traction battery.

A processing device performing driving environmental data related processing related to a local driving environmental data provided with data in an autonomous driving mode of a host vehicle is provided. The processing device includes a processor and a storage medium. The processor is configured to provide update to the local driving environmental data of a planned driving area where the host vehicle is planned to travel, based on probe information recognized through sensing by the host vehicle, among the local driving environmental data stored in the storage medium; and adjust a control level for each type of driving task, which is controlled according to a driving scene of the host vehicle in the autonomous driving mode, to an individual correlation level that correlates with an update count of the local driving environmental data of the planned driving area.

The invention discloses a Yellow River water conservancy project real-time monitoring system based on edge computing, and particularly relates to the technical field of cloud computing. The system constructs a flow state characteristic interval by collecting water and sediment data; loading an algorithm component based on flow state characteristics, and changing a master control pointer by using atomization operation to realize calculation power logic hot switching; analyzing a difference value between the instantaneous torque of the motor and the no-load reference to obtain a sediment deposition resistance torque; mapping the resistance moment to a digital shadow table to extract a gain compensation parameter; and resetting controller parameters and modulating the pulse width signal according to the compensation coefficient, and outputting a driving voltage to control the gate. Through the edge end algorithm hot switching technology, the problems that a traditional system is difficult to adapt to the variable water and sediment working conditions of the Yellow River and logic updating shutdown are solved, and monitoring continuity is guaranteed. The defect of power mismatching of a single driving mode is overcome, motor overload and mechanical jamming are prevented, gate control accuracy and operation stability are greatly improved, and the service life of equipment is greatly prolonged.

The invention relates to the technical field of self-balancing two-wheeled vehicle control, and discloses a self-balancing two-wheeled vehicle control system based on autonomous following reinforcement learning, and the system comprises a sensing and positioning module which is used for collecting and processing multi-source sensor data in real time, and generating vehicle state information; the behavior decision module is used for constructing a driving mode decision for guiding a macroscopic driving behavior; the motion planning and control module is used for generating an actual motion instruction for driving the vehicle; the execution module is used for analyzing the generated actual action instruction and converting the actual action instruction into a driving signal for the self-balancing two-wheeled vehicle; and the vehicle state and dynamics model module is used for managing vehicle state information. A dynamic stability domain predictor is introduced, and bidirectional information coupling between a high-level strategy network and the predictor is established, so that an expected action instruction generated by a high-level decision is constrained in a physically feasible safe action space in real time before execution, and the physical stability of a vehicle in a complex dynamic state is ensured through a closed-loop feedback mechanism.

The invention provides a mode switching method, a vehicle and a storage medium, the method is applied to the technical field of hybrid power control, and the method comprises the steps that under the condition that a control instruction for switching a driving mode of the vehicle from a direct driving mode to a series connection mode is received, the direct driving mode is switched to the series connection mode; the method comprises the following steps: determining the discharge power of a power battery of a vehicle and the whole vehicle driving power of the vehicle, determining a target interval where the whole vehicle driving power is located based on the discharge power of the power battery and the whole vehicle driving power, determining a target torque reduction gradient corresponding to the target interval, and then determining the torque reduction speed of the vehicle based on the target torque reduction gradient. And the actual torque of the engine is controlled to be reduced to the target torque, and under the condition that the actual torque of the engine is equal to the target torque, the clutch is controlled to be in an open state, so that the driving mode of the vehicle is switched to the series connection mode from the direct drive mode. According to the method, the torque can be reduced gently, and power interruption caused by the fact that the engine torque is directly reduced to zero is avoided.

A method of controlling a vehicle with a plurality of motion actuators comprises: determining a longitudinal inclination and speed of the vehicle; selecting an uphill drive mode if the longitudinal inclination is greater than an inclination threshold and the absolute speed is less than a speed threshold, and otherwise selecting a regular drive mode; obtaining motion requests; in accordance with the selected drive mode, providing a solution to an optimization problem related to optimal control of the motion actuators in accordance with the obtained motion requests; and controlling the motion actuators in accordance with the solution to the optimization problem. The optimization problem is dependent on a control effectiveness matrix which is defined differently in the uphill drive mode and the regular drive mode.

The invention discloses a braking energy distribution method and system based on braking noise prediction and electronic equipment. The method comprises the steps that braking noise time sequence data, vehicle speed time sequence data, hydraulic braking torque time sequence data and pedal travel time sequence data of a current vehicle are obtained; inputting the braking noise time sequence data, the hydraulic braking torque time sequence data and the pedal travel time sequence data into a pre-trained braking noise prediction model to obtain a braking noise prediction value of the current vehicle after a preset time step; determining a corresponding braking noise threshold value according to the current working condition and the current driving mode of the current vehicle; and when the braking noise prediction value is larger than the braking noise threshold value, the braking energy distribution proportion is adjusted, so that the energy recovery torque is increased, and the hydraulic braking torque is reduced. According to the method, the braking noise of the vehicle is maintained below the threshold value through dynamic distribution of the braking energy, interference to users in the vehicle is avoided, the driving comfort of the vehicle is improved, and the method can be applied to the technical field of vehicle control.

The invention discloses a dual-drive self-switching strong-adaptability quadruped robot motion control method, which comprises the following steps of: estimating current topographic features by using sensing signals such as body state feedback, IMU (Inertial Measurement Unit) and sole force, and predicting a falling probability according to the topographic features, so that a quadruped robot is intelligently switched between two driving modes of MPC (Moving Picture Control) independent control and MPC-DRL (Moving Picture Control-Digital Regulation Language) cooperative control; dynamic behavior parameters are introduced to influence the gait and step height of robot movement, the optimization efficiency and smoothness of MPC and the disturbance adaptive capacity of DRL are efficiently fused, and the high-robustness, high-efficiency and self-adaptive movement capacity of the quadruped robot in various terrains under the condition that external sensing information is not relied on is enhanced.

An automotive power system integrates a power factor correction circuit, an H-bridge power module, an externally excited synchronous machine, a traction inverter, and a traction battery. The system operates in two modes: driving and charging. In driving mode, power flows from the traction battery through the H-bridge power module and the traction inverter to the externally excited synchronous machine, enabling vehicle propulsion. In charging mode, power from an AC source is routed sequentially through the power factor correction circuit, the H-bridge power module, the synchronous machine, and the traction inverter.

The invention relates to the technical field of high-voltage switch equipment, and discloses a primary and secondary fusion pole-mounted circuit breaker which comprises a base, a front plate is arranged on the front side of the base, the base and the front plate are connected through a connecting plate, a first solid-sealed polar pole is arranged on the top of the base, and a second solid-sealed polar pole is arranged on the top of the front plate. A high-voltage input plate is arranged at the top of the solid-sealed polar pole I, a high-voltage output plate is arranged on one side wall of the solid-sealed polar pole I, the connecting frame is fixedly connected between the solid-sealed polar poles I, the bird repelling mechanism is arranged at the top of the connecting frame and used for repelling birds to prevent the birds from stopping, and the shielding mechanism is arranged at the top of the solid-sealed polar pole I. By means of the bird repelling mechanism, the all-weather and intelligent active bird repelling function is achieved, stable equipment operation is guaranteed, a dual-drive mode combining wind power and solar power is adopted, it is guaranteed that the bird repelling function is uninterrupted, pollution flashover or short circuit faults caused by bird activities to high-voltage insulation parts are effectively avoided, and the equipment operation reliability is improved.

The invention discloses a container terminal truck intelligent scheduling method and system based on multiple driving modes. The method comprises the steps that a whole-process system architecture integrating a central scheduling platform, a vehicle-mounted intelligent terminal and a sensing and communication network is constructed; the method comprises the following steps: acquiring basic data of vehicles, tasks, road networks and environments, constructing a multi-objective optimization function, establishing a dangerous goods risk integral model, respectively setting mathematical constraints for task assignment, path planning, hybrid driving coordination, dynamic path tracking and mode switching, and forming a multi-dimensional mathematical model; an improved non-dominated sorting genetic algorithm is adopted to solve the model, and a personalized scheduling scheme including vehicle-task assignment, path planning, time requirements and risk control rules is generated; through cooperation of the central scheduling platform and the vehicle-mounted intelligent terminal, MPC dynamic path tracking is adopted for the unmanned vehicle, visual and voice dual-mode guidance is provided for the artificial vehicle, and hybrid driving cooperative management and control are implemented, so that the vehicle operation efficiency and the dangerous goods transportation safety are guaranteed.

The invention discloses a control method, device and equipment of a hybrid electric vehicle and a storage medium, and relates to the technical field of hybrid electric vehicles, and the control method comprises the steps that the current driving mode, the current SOC, the current vehicle speed, the whole vehicle demand power and environment information of the vehicle are obtained; determining a vehicle state according to the environment information, the current driving mode and the current SOC; a range extender starting strategy is determined according to the vehicle state, and a range extender of the vehicle is controlled; when an engine of the range extender is started, determining a target operation mode and power generation power of the range extender according to the current vehicle speed and the required power of the whole vehicle; and determining the power generation rotating speed of the range extender according to the environment information and the power generation power of the range extender, and controlling the engine. The technical problems of low energy management efficiency and unstable operation caused by the fact that fixed threshold value control cannot adapt to environmental changes are solved, accurate matching of range extender start-stop control and power generation strategies under complex environmental conditions is achieved, and the energy utilization efficiency and the operation stability of the whole vehicle are improved.

The invention relates to a vehicle braking control method and device, computer equipment and a storage medium. The method comprises the steps that in response to a braking instruction of a vehicle, target braking deceleration of the vehicle is determined according to braking pedal information and driving mode information of the vehicle; determining a target braking force and a target braking torque of the vehicle according to the target braking deceleration, the whole vehicle mass and the wheel rolling radius of the vehicle; under the condition that the target braking deceleration is larger than a preset deceleration threshold value, the mechanical braking torque of the vehicle is determined according to the target braking torque and the energy recovery torque; according to the real-time acceleration of the vehicle, the wheel static load is corrected, and the wheel dynamic load of the vehicle is obtained; according to the mechanical braking torque and the wheel dynamic load, the mechanical braking force of each wheel of the vehicle is determined; the mechanical braking force is used for controlling the vehicle to conduct mechanical braking, and the braking effect of the vehicle is improved.

A system is provided for determining a loading location of a workpiece relative to a holding fixture, comprising: a robot including a sensor; and a controller coupled to the robot and configured to activate the robot to grip the workpiece; enable a free-drive mode to permit an operator to move the gripped workpiece to a starting location; execute a center location routine including causing the robot to: move in a first direction until the sensor senses contact with a first surface of the holding fixture; move in a second direction until the sensor senses contact with a second surface; move in a third direction until the sensor senses contact with a third surface; and compute a three-dimensional center point of the holding fixture representing the loading location of the workpiece using the first, second and third sensed positions of contact.

Embodiments of the disclosure may provide a display device comprising a first display panel configured to display a first image; a second display panel configured to display a second image; a gate driving circuit configured to supply gate signals to the first display panel and the second display panel; a first data driving circuit configured to supply a first data voltage to the first display panel; a second data driving circuit configured to supply a second data voltage to the second display panel; a gamma circuit configured to supply gamma voltages to the first data driving circuit and the second data driving circuit; and a timing controller configured to supply image data to the first data driving circuit and the second data driving circuit, and control the gamma circuit to change the gamma voltages supplied to the first data driving circuit and the second data driving circuit depending on driving modes.

The utility model discloses a lifting type connection table which comprises a table body, a lifting mechanism and two connection assemblies arranged on the table body. Wherein one connection assembly is fixedly installed on the table body, the other connection assembly is hinged to the table body, the lifting mechanism is installed on the table body, and the output end of the lifting mechanism is connected with the connection assembly hinged to the table body and can drive the connection assembly to rotate with the hinge point as the center. According to the utility model, through the lifting mechanism and the lifting of one connection assembly, the connection requirements of different heights and angles are met; automatic lifting is achieved through an air cylinder or hydraulic cylinder driving mode, manual intervention is reduced, and the operation efficiency is improved. The distance adjusting assembly is adopted in the connection assembly, accurate adjustment is achieved in a ball screw motor mode, and the conveying requirements of different sizes are met.

The invention provides a cooperative control method and system for an electric trailer and a main vehicle and a vehicle, and relates to the technical field of new energy vehicles and intelligent control. The method comprises the steps that the states of a main vehicle and an electric trailer are obtained, and when the states meet preset state conditions, a driving mode is entered; in the driving mode, the main vehicle electric driving system and the electric trailer electric driving system are controlled to output driving torque based on the torque required by a driver and a torque distribution strategy; acquiring a braking request signal and mode switching information; if the braking request signal indicates that the multi-stage energy recovery switch is pressed down or the brake pedal is stepped down and the mode switching information meets a first switching condition, switching to a braking mode; if the mode switching information meets a second switching condition, switching to a driving mode; and in the braking mode, the main vehicle electric driving system and the electric trailer electric driving system are controlled to conduct braking energy recovery based on the required braking torque and the allowable recovery power of the battery. The control efficiency and the system adaptability are improved.

The invention relates to the technical field of electronic display, and discloses a liquid crystal display screen display control system based on multi-mode driving. The system comprises a content feature analysis module, a mode decision engine, a driving parameter library and a liquid crystal driving signal generation module. Multi-dimensional feature vectors are extracted through the content feature analysis module, a nonlinear decision mechanism combining fuzzy reasoning and hysteresis control is adopted, and single fixed threshold judgment in the prior art is thoroughly abandoned. The system can accurately capture dynamic characteristics of display content, effectively avoids the problem of mode oscillation in a threshold critical region, and realizes smooth and stable switching of driving modes. According to the invention, the hysteresis comparator and the continuous frame decision logic are introduced, so that the anti-interference capability and decision stability of the system are remarkably enhanced. The system does not trigger mode switching due to instantaneous noise or slight jitter of a single-frame image, so that the continuity of display experience is ensured, and extra power consumption caused by frequent switching is reduced.

The invention discloses a laser cutting device for automobile parts, and relates to the technical field of laser cutting. The device comprises a machine tool, and the upper end of the machine tool is fixedly connected with a waterproof tabletop; and the pipeline clamping mechanism comprises a supporting seat fixedly connected to the waterproof table top, a rotating cylinder used for a pipeline to penetrate through is rotationally installed on the supporting seat, an electric three-jaw chuck is fixedly connected to the end of the rotating cylinder, and a driving piece used for driving the rotating cylinder to rotate and a pushing piece used for driving the pipeline to move are installed on one side of the machine tool. The double-driving mode of rotation and translation is achieved through the electric three-jaw chuck and a double-end clamping structure abutting against the rolling wheel base, angle adjustment and telescopic movement of the laser cutting head can be achieved through the hinge base and the telescopic frame, hollow-out cutting and special-shaped cutting operation of the pipeline can be achieved in cooperation with the translation driving mode of the pipeline, and the working efficiency is improved. And the flexibility and functionality of the device are improved.

The invention discloses a control method of a hybrid power vehicle and the hybrid power vehicle. The control method of the hybrid power vehicle comprises the steps that the SOC of a battery pack is obtained; confirming that the vehicle enters a motor driving mode; and controlling the maximum speed of the vehicle according to the SOC of the battery pack. According to the control method of the hybrid vehicle, the probability that the driving force of the vehicle is rapidly attenuated due to the fact that the electric quantity of the battery pack is consumed too rapidly in the low-electric-quantity state can be reduced, and the safety and the driving experience in the vehicle running process are improved.