1538 results about "Emergency brake" patented technology

The invention relates to the technical field of vehicle safety, and discloses a braking method and system based on vehicle automatic emergency early warning and braking and a storage medium. The method comprises the following steps: fusing multi-modal sensor data to generate a dynamic environment perception graph and calibrating the dynamic environment perception graph; generating a real-time risk distribution map and a potential collision probability prediction matrix based on the dynamic risk assessment model; carrying out matrix multi-stage decision optimization to generate emergency braking trigger conditions, and dividing early warning levels and scheduling according to the conditions and a risk map; and the braking system control parameters are adapted according to the early warning instruction set, and a final execution scheme is generated after verification. The system comprises a sensing module, an evaluation module, a decision module, an early warning module and an execution module. Electronic equipment and a computer readable storage medium can execute the method. Through multi-modal fusion, dynamic risk assessment, graded early warning and redundancy check, the safety performance of the vehicle in a complex environment is improved, accurate early warning and reliable braking are achieved, and the method is suitable for the technical field of vehicle safety.

The invention discloses an unmanned vehicle intelligent obstacle avoidance method and system based on a multi-modal sensor, and relates to the field of automatic driving and intelligent traffic. According to the technical key points of the invention, data of a laser radar and a depth camera are aligned through a space-time registration module; the laser radar point cloud is preprocessed, obstacle point cloud is segmented, fusion clustering is carried out in combination with three-dimensional semantic seed points output by a depth camera, and an obstacle cluster with a semantic tag is generated; and calculating a three-dimensional directed bounding box (OBB) of an obstacle, dynamically adjusting a safety distance according to the speed of the vehicle, expanding the OBB of the vehicle, and carrying out collision detection by adopting a separation axis theorem. When a collision risk is detected, the system sequentially triggers a first-level early warning instruction and a second-level emergency braking instruction, and safe and efficient unmanned vehicle dynamic obstacle avoidance is achieved. According to the method, the advantages of multiple sensors are fully utilized, the obstacle detection precision and the response speed are effectively improved, and reliable technical support is provided for application of the unmanned driving technology in a complex road environment.

The air quality intelligent monitoring system based on sensing data feedback comprises a sensing array module, a preprocessing module, a risk assessment module, an energy consumption decision module, a mode switching module, a data fusion module and a linkage module. The sensing array module generates an environment parameter signal; the preprocessing module generates a standardized characteristic signal; the risk assessment module receives the standardized characteristic signal and forms an early warning instruction signal; the energy consumption decision module analyzes the change gradient of the standardized feature vector and generates an activation instruction according to the vector stability; the mode switching module generates a state configuration signal and feeds back the state configuration signal to the sensing array module; fusing the data to generate a diffusion prediction signal; the linkage module generates an emergency braking instruction and transmits the emergency braking instruction back to the data fusion module. The intelligent air quality monitoring system based on sensing data feedback can solve the problem that intelligent linkage of multi-source pollution monitoring, dynamic energy saving and real-time early warning of industrial places is poor.

The invention provides a vehicle driving control method and device for a backlight scene, equipment and a medium. The method comprises the steps that multi-source information of a target vehicle is acquired in real time; performing fusion calculation on the multi-source information to obtain a current backlight risk index of the target vehicle; determining a driving assistance strategy or an automatic emergency braking strategy based on the backlight risk index; and controlling the target vehicle according to the driving assistance strategy or the automatic emergency braking strategy. According to the vehicle driving control scheme for the backlight scene, the backlight risk index is generated by fusing the multi-source information, the backlight scene is accurately judged, the corresponding driving assistance or automatic emergency braking strategy is formulated, the driving safety and reliability of the vehicle in the complex backlight environment are improved, and the driving safety of the vehicle in the complex backlight environment is improved. The problems that in the prior art, due to dependence on a single sensor in a backlight scene, the target recognition precision is low, a dynamic adaptation mechanism is lacked, and a braking strategy is difficult to pre-judge and adjust in advance are solved.

The invention provides a train operation control method and device under severe weather, and the method comprises the steps: obtaining train idling slip information sent by a train automatic protection subsystem or a train control and management system, and determining a rail slippery state according to the train idling slip information; determining a severe weather mode instruction of the target train based on the rail slippery state and the weather state; and sending a severe weather mode instruction to the train automatic protection subsystem or the train control and management system, wherein the severe weather mode instruction is used for indicating a target train in the target operation area to enter a severe weather mode. According to the train operation control method and device in the severe weather, the severe weather mode instruction of the target interval is determined according to the wet and slippery state of the rail and the weather state, safety protection can be carried out on the guaranteed emergency braking rate in the severe weather, and the situation that due to the fact that the train braking adhesion coefficient is reduced to break through the existing design boundary, the train operation efficiency is improved is avoided. Therefore, the safety of train operation is improved.

The invention relates to the technical field of photovoltaic module manufacturing, in particular to a lamination process parameter self-adaptive regulation and control system and method. Comprising a multi-source sensing module, an edge calculation module and a dynamic execution module, and temperature, pressure and thickness data of a lamination process are collected in real time through an infrared thermal imaging unit, a distributed pressure sensing unit and an ultrasonic thickness monitoring unit; the edge calculation module adopts a CNN-LSTM hybrid model to perform spatial-temporal feature fusion analysis on the multi-source data, predicts a defect risk level and generates a regulation and control instruction; the dynamic execution module achieves dynamic parameter adjustment through the partition temperature control unit, the hydraulic servo unit and the emergency braking unit, the problems of parameter stiffness, defect detection lag and the like of a traditional lamination process are solved, the AOI spot check defect rate is reduced to 0.6% from 1.3%, the lamination period is shortened by 3 minutes, and the production efficiency and the product quality are remarkably improved.

The invention relates to the technical field of data processing, in particular to a PSU pressurization module and a control method thereof, and the PSU pressurization module comprises a data acquisition unit, a dynamic compensation unit, a cooperative control unit, a pressure closed-loop unit and an emergency response unit. The data acquisition unit is used for acquiring an energy accumulator pressure value, an environment temperature value and a braking command signal in real time; the dynamic compensation unit generates a viscosity compensation coefficient through a temperature and viscosity mapping table, and compares the viscosity compensation coefficient with the pressure value to generate a pressure deviation value and a deviation trigger threshold value; the cooperative control unit activates the hydraulic pump based on the pressure deviation value and adjusts the start-stop frequency in combination with the viscosity compensation coefficient; the pressure closed-loop unit adopts double electromagnetic valves to alternately release and supplement oil to inhibit pressure fluctuation; the emergency response unit activates the hydraulic pump and opens the bypass electromagnetic valve to output redundant flow during emergency braking, the technical limitation of an existing hydraulic system in an extreme environment is broken through, and the braking reliability is improved.

The invention discloses an intelligent control method and system for motorcycle calipers. According to the method, multi-modal data such as vehicle speed, wheel speed, piston displacement, brake disc temperature, inclination angle and transverse acceleration are collected in real time through a multi-source sensor and are preprocessed; calculating a braking demand and an adhesion coefficient according to the data, and recognizing a straight line, a curve or an emergency braking scene in combination with the inclination angle and the transverse acceleration; inputting the data into a pre-trained brake control machine learning model to generate a target brake force change curve; controlling the driving motor and the calipers to brake based on the curve, and regularly optimizing the model according to brake feedback and historical data; predicting a braking efficiency attenuation trend by combining a part degradation model, and compensating the braking force to update the model; the motor current is adjusted in real time through closed-loop control so as to follow the target braking force; and continuously monitoring the temperature of the brake disc, and triggering thermal attenuation compensation when the temperature exceeds a threshold value. According to the invention, self-adaptive, accurate and reliable intelligent braking of the motorcycle is realized.

The invention provides an emergency braking control method, which is realized by using an emergency braking loop structure, and the emergency braking loop structure comprises a control loop connected with an occupied end and an action loop for connecting emergency braking electromagnetic valves of vehicles in parallel; a positive electrode power supply and a negative electrode power supply are provided for the control loop through the occupied end, and the control loop enables the two ends of an emergency braking loop relay to be powered on by connecting monitoring conditions and train lines in series; the action loop is used for connecting the emergency braking electromagnetic valves of all the vehicles in parallel, and when the relay of the emergency braking loop loses power, the normally open contact is disconnected, the emergency braking electromagnetic valves of all the vehicles lose power, and emergency braking is generated; according to the method, the problems and defects of an emergency braking loop of an existing motor train unit project can be solved, a specific monitoring function is executed through the emergency braking loop independent of a train control system, and the emergency braking loop adopts a control mode of a hardware relay control circuit, so that safe stopping of a motor train under the fault condition is guaranteed.

The invention relates to the technical field of vehicle safety, in particular to a vehicle autonomous emergency braking-oriented road surface attachment sensing method, which comprises the following steps of: acquiring all initial point cloud data in a preset sensing area in front of a vehicle by using a laser radar at the top of the vehicle, and segmenting the initial point cloud data to obtain a road surface point cloud data set in the preset sensing area; acquiring a reflected light intensity value of each piece of road surface point cloud data in a preset sensing area, and taking the road surface point cloud data of which the reflection intensity value is not in a high reflection intensity threshold range but is in a road surface reflection intensity threshold range as target point cloud data; based on the reflection intensity values of all the target point cloud data, generating a grayscale image, inputting the grayscale image into a classification model, outputting a pavement type prediction result, determining a pavement adhesion coefficient, and calculating brake pressure; and if the distance between the current vehicle and the front vehicle is smaller than the safe distance, the vehicle performs autonomous emergency braking based on the braking pressure. The safety and comfort of emergency braking are improved.

The invention discloses a train protection zone processing method based on a train-to-train communication architecture, which comprises the following steps that: an ATP (Automatic Train Protection) of a fault train submits an application for requesting to establish a protection zone to an RC (Remote Control), and the RC sends inquiry information to all trains which establish communication with the RC in a control zone of the RC; after receiving inquiry information of the RC, the trains check the relation between the trains and the protection area and reply, and if all the trains reply to agree to establish the protection area, the RC establishes the protection area; according to the distance between the train inside and outside the protection area and the fault train and the corresponding driving direction, the running state of the train is determined; the running state is emergency braking or continuous running; and after the fault train does not report derailment to the RC or an obstacle exists on the track, the protection area of the fault train is cancelled. The safety and efficiency of train operation are improved.

The invention relates to the technical field of urban rail train safety detection, and discloses a mechanical rail train detection method and system with a real-time detection function, and the method comprises the steps: collecting the states of obstacles on the two sides of a bogie and normally open and normally closed contacts of derailment detection travel switches; calculating a trigger state code; an emergency or non-emergency braking signal is output and an alarm is given; and when the state returns to normal and a reset instruction is received, the alarm is released and the initial state is recovered. In the prior art, obstacle or derailment detection is realized by depending on a multi-stage sensor and an electronic control unit, and especially in complex operation environments of high electromagnetic interference, high humidity dust and the like, stable and low-fault-rate real-time detection cannot be realized. Due to the fact that a redundancy judgment mechanism combining a pure mechanical structure and the vehicle programmable logic control unit LCU is adopted, high-reliability real-time detection of the obstacle and derailment state is achieved, and the safety and maintainability of a train system are improved.

The invention relates to an automatic emergency braking threshold value adjusting method and system based on in-cabin multi-mode information, and relates to the technical field of auxiliary driving, the method comprises the steps that visual information and audio information of a driver and at least one passenger in a cabin are obtained, the visual information comprises facial expressions and head postures, and the audio information comprises audio information of the driver and the at least one passenger; the audio information comprises voice features and non-voice sounds; respectively calculating a driver state coefficient and a passenger state coefficient based on the visual information and the audio information; fusing the driver state coefficient and the passenger state coefficient to obtain an in-cabin safety situation coefficient; and according to the in-cabin safety situation coefficient, a triggering threshold value of the automatic emergency braking system is adjusted in a self-adaptive mode. According to the method, multi-modal information such as vision and audio in the cabin is fused, and state analysis of all passengers is combined, so that intelligent self-adaptive adjustment of the AEB braking threshold value can be realized, and the sensing accuracy and decision reliability of an emergency braking system in a complex scene are improved.

The invention relates to a vehicle active safety control method and system, a storage medium and a vehicle, and belongs to the field of intelligent driving control. The vehicle active safety control method comprises the steps that driving state information is obtained in real time; calculating a longitudinal risk avoidance determination threshold based on the driving state information, and setting a first trigger condition based on the longitudinal risk avoidance determination threshold; if the longitudinal distance between the vehicle and the target vehicle meets the first triggering condition, an automatic emergency braking system is activated, and a first deceleration used for controlling longitudinal braking of the vehicle is generated; after the automatic emergency braking system is activated, a transverse risk avoiding judgment threshold value is calculated on the basis of the driving state information updated in real time, and a second triggering condition is set on the basis of the transverse risk avoiding judgment threshold value; if the longitudinal distance between the vehicle and the target vehicle meets a second triggering condition, an automatic emergency steering system is activated, and a second control instruction is generated; wherein the second control instruction is used for controlling the automatic emergency steering system to execute the cooperative steering angle and controlling the automatic emergency braking system to execute third deceleration cooperating with the cooperative steering angle.

The invention belongs to the technical field of vehicles, and particularly relates to an ABS function trigger control method and device, a vehicle and a medium. The method comprises the following steps: calculating a wheel slip rate; determining driver intention according to the hydraulic sensor signal, the brake pedal sensor signal and the accelerator pedal sensor signal, wherein the driver intention comprises emergency braking, conventional braking, sliding and acceleration; the road bumping state is determined according to the wheel slip rate, the vehicle vertical acceleration and the suspension displacement; according to the intention of the driver and the road bumping state, the triggering condition of the ABS function is determined; and determining whether the triggering condition of the ABS function is met or not according to the wheel slip rate. By judging the intention of the driver and the road bumping state and adjusting the triggering condition of the ABS function in real time according to the intention of the driver and the road bumping state, false triggering of the ABS function when the vehicle passes through the bumping road is avoided.

The invention relates to the technical field of automation control, and discloses a photovoltaic panel cleaning robot control method and system and a robot, and the method comprises the following steps: S1, collecting photovoltaic panel surface image data in real time through a multi-mode visual sensor module carried on a cleaning robot, generating a cleaning grade, and matching a corresponding cleaning strategy; s2, a multi-sensor fusion module is used for monitoring the surrounding environment of the robot in real time, and the motion trail of the robot is adjusted or emergency braking is triggered for intelligent obstacle avoidance; and S3, updating the environment map in real time based on a self-adaptive path planning algorithm combining an A * algorithm and reinforcement learning so as to realize full-coverage cleaning and avoid repetition or omission. The multi-modal visual sensor module is combined with a deep learning algorithm to realize accurate recognition of stains and obstacles, a dynamic cleaning strategy is generated, and through Q-learning training, the cleaning time is shortened and repeated operation is avoided, so that the cleaning efficiency and the coverage rate are improved.

The invention discloses an axle staged cooling system, an axle staged cooling assembly and an engineering vehicle. The axle staged cooling system comprises an engine first-stage cooling system, an engine second-stage cooling system, an axle first-stage cooling system and an axle second-stage cooling system. Each stage of cooling system controls cooling water and oil path trend through a thermolator in each loop, controls axle cooling oil and engine cooling water to exchange heat, and meets different cooling requirements of an axle. The temperature sensor in each loop outputs water and oil temperature signals to a motor of the cooling fan, so that the rotating speed of the fan is increased to different degrees along with the temperature rise of each cooling system, and different cooling powers are matched. According to the grading system, the engine and the axles can work at the proper temperature at the same time, the two heat exchangers cool cooling oil of the front axle, cooling oil of the middle axle and cooling oil of the rear axle respectively, the cooling capacity of the front axle is improved, the braking effectiveness of the front axle is guaranteed, and rollover caused by serious backward movement of the gravity center of a vehicle during emergency braking is prevented.

A lighted steering wheel device is provided. The device is comprised of a steering wheel that integrates customizable and functional lighting features to enhance both safety and aesthetics. The steering wheel comprises various materials and configurations, with embedded flexible LED strips encased in impact-resistant, UV-protected casings, capable of displaying a wide range of static or dynamic light patterns. These patterns can be synchronized with vehicle systems, such as flashing red for emergency braking or reacting to turn signals, and brightness can adjust based on vehicle speed. The device includes a control interface embedded in the wheel and offers further customization via a mobile app, which provides remote access to light settings and synchronization features. Additionally, the device can generate safety alerts, utilizing proximity sensors, GPS integration, and haptic feedback for a multisensory driver experience, with an illuminated emblem adding a complementary design element.

The invention discloses a vehicle braking method, device and equipment and a readable storage medium. The vehicle braking method comprises the steps that when a main braking controller detects that a first brake pedal travel sensor signal is invalid, and a backup braking controller detects that a second brake pedal travel sensor signal is invalid; when the main brake controller detects that the duration of the first signal of the mechanical brake lamp switch is longer than the preset duration, the vehicle is controlled to be braked emergently; wherein the mechanical brake lamp switch is installed on the brake pedal, when the brake pedal is in a treading state, the mechanical brake lamp switch provides a first signal, and when the brake pedal is not in the treading state, the mechanical brake lamp switch provides a second signal. According to the brake control method and device, when the first brake pedal travel sensor signal and the second brake pedal travel sensor signal are invalid, the brake intention is recognized in time through the brake lamp switch connected with the main brake controller through the hard wire, emergency braking is applied to the vehicle, and the safety of vehicle braking is ensured.

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 belongs to the technical field of anti-collision monitoring of cranes, and particularly discloses an anti-collision monitoring method for a crane on a dock platform, which comprises the following steps: S1, monitoring the environment around the crane in real time through a sensor, and obtaining obstacle information around the crane; s2, performing data fusion and analysis on data acquired by different sensors; s3, calculating a collision risk according to the movement track of the crane and the position and speed of the obstacle, and giving an alarm when a potential collision risk is detected; s4, integrating S3 with a control system of the crane, and automatically controlling a starter to perform emergency braking; the anti-collision monitoring method can be operated more efficiently and reliably. The sensor provides environment sensing capability, the data processing module realizes intelligent analysis, the early warning and control module ensures safe operation, and the design can effectively reduce the collision risk of the crane on the dock platform and improve the operation safety.

The invention relates to the technical field of vehicles, and discloses a vehicle-mounted image generation device, a vehicle machine system and a vehicle. The method comprises the following steps: at least acquiring first point cloud data and first image data through a data fusion module, and converting the two data into a bird's-eye view feature map through a preset conversion algorithm; performing semantic analysis on the user voice through a preset semantic analysis model by using a voice analysis module; generating a vehicle-mounted application image at least applied to head-up display and / or screen display according to the bird's-eye view feature map and the semantic analysis result by using an image generation engine through a preset compression model; and terminating the generation process of the vehicle-mounted application image in a preset time period after the automatic emergency braking signal is received through the emergency interruption module, and at least applying the graphic processing computing power of the generation process to a vehicle collision avoidance decision. Therefore, the problem that in an existing vehicle-mounted image generation technology, due to the fact that the computing power is too large, vehicle decision making is not timely under the emergency situation can be solved, and the driving safety of a user can be guaranteed.

The invention discloses an automatic emergency braking system and method based on a graph neural network and retrieval enhancement generation. Comprises: a dangerous scene map construction module for extracting target spatial-temporal characteristics based on an accident video, marking on a high-precision map, and constructing a dangerous scene map; the GNN encoding module encodes the dangerous scene into an embedded vector and stores the embedded vector in a cloud vector database; the real-time positioning and retrieval module is used for calculating a retrieval radius and indexing and downloading nearby scene subsets; the real-time sensing module is used for generating a structured sensing data frame through time-space synchronization and multi-sensor fusion; the real-time GNN coding and similarity matching module is used for carrying out similarity matching on the coded current scene and the subset and calculating a safety evaluation coefficient; and the decision optimization module is used for triggering the active intervention strategy according to the priority based on the safety evaluation coefficient. According to the method, advanced perception and active avoidance of potential risks are realized by retrieving historical dangerous scene experience, and the driving safety in a complex scene is remarkably improved.

The invention relates to the technical field of control system data processing, in particular to a ship intelligent workshop crane hoisting path planning method, which comprises the following steps: collecting crane coordinates, obstacle distribution, load swing angle and material weight, and inputting a physical constraint model to generate a structured environment state data set; initializing wolf pack algorithm parameters based on the structured environment state data set, calculating a compressed detection wolf walking step length according to an obstacle distance, generating a global task queue by an industrial cloud platform according to a dynamic parameter set, and outputting an execution state data set by a crane end; counting emergency braking times from an execution state data set to optimize a walk step length function, comparing task time to optimize a wolf investigation proportion, analyzing historical swing data to establish a step length and swing mapping library, and optimizing a parameter set to feed back and update a physical constraint model. According to the invention, cooperation of environment perception, dynamic path planning and closed-loop verification is realized, and accident risks and production delay in a ship workshop narrow space dynamic obstacle scene are reduced.

The embodiment of the invention relates to the technical field of vehicle intelligent control, and discloses a vehicle remote control parking system, a control method and equipment, and the system comprises an intelligent driving domain control SOC and an intelligent driving domain control MCU which are in communication connection; the intelligent driving domain control MCU is provided with an ultrasonic algorithm module, a CAN signal processing module, a first remote control parking module, an arbitration module and a vehicle control module. The first remote control parking module arranged in the intelligent driving domain control MCU can independently receive obstacle distance data of the ultrasonic algorithm module and vehicle state signals of the CAN signal processing module, a basic parking track is rapidly generated, waiting for starting of the intelligent driving domain control SOC is not needed, the waiting time of the system is shortened, and the parking efficiency is improved. The basic parking track is strictly verified through the arranged arbitration module, the execution of unsafe tracks exceeding a threshold value is refused, and when the arbitration module judges that the collision risk exists according to the obstacle distance data, the emergency braking instruction is immediately triggered, collision is avoided, and the automobile function safety standard is met.

The invention discloses an intelligent unmanned remote control system and method for an oil field electric workover rig, and relates to the field of remote control of the oil field electric workover rig, and the system comprises a full-dimension sensing network construction module, a digital twin driving cognition module, an edge intelligent decision module, and a man-machine co-fusion interaction module. According to the intelligent unmanned remote control system and method for the electric workover rig in the oil field, a three-level decision-making tree designed by dynamic priority task scheduling sets extremely short response time for different level requirements of emergency braking, working condition adjustment and parameter optimization, various sudden and conventional operation change conditions can be rapidly dealt with, and the operation efficiency is improved. By establishing a comprehensive multi-objective optimization function, energy consumption, operation time and risk indexes can be comprehensively considered, weight coefficients can be flexibly adjusted according to different operation scenes and user requirements, and equipment operation parameters and operation process control schemes which meet multi-objective optimization and conform to equipment and operation safety and performance constraint conditions can be accurately searched.

A locking device for a stationary bicycle may include a housing having a knob receiving wall and a sidewall. The sidewall has a first end connected to the knob receiving wall and a second end forming an opening. The knob receiving wall is located opposite the opening of the housing. A chamber is configured to receive a knob of the stationary bicycle. A first latch is connected to the outer wall surface of the sidewall of the housing. A lock device may include a base having an aperture configured to receive at least a portion of the rod. The first latch of the housing is removably connected to a capturing structure of the base. The knob receiving wall of the housing is configured to connect to the knob and depress the knob to engage an emergency brake of the stationary bicycle when the housing is connected to the base.

The utility model discloses a driverless formula car braking system, including adjustable slide rail, brake pedal and brake actuating mechanism, adjustable slide rail is provided with foot support, first base and second base in proper order, brake pedal bottom is connected with first base through brake stay bar, brake stay bar one end is connected with first base, brake stay bar one end is connected with second base, brake stay bar one end is connected with second base, brake stay bar one end is connected with second base, brake stay bar one end is connected with the brake actuating mechanism. The other end is connected with the brake actuating mechanism; the brake executing mechanism is connected with the second base through a mounting support, the brake supporting rod is connected with two brake main cylinders through a brake balance rod arranged in a penetrating mode, and a brake air cylinder is arranged below the foot support and located at the bottom of the brake balance rod. According to the unmanned formula car braking system, a manned mode braking system and an unmanned mode braking system are designed to be connected in parallel, normal braking and emergency braking are freely switched under the unmanned condition, mutual interference is avoided in the mechanical structure, the positions of pedals and sliding rails are adjustable, all parts are modularly designed, and the braking system is convenient to use and easy to popularize. Disassembly and assembly are convenient, and the driving experience of a driver is high.

The invention relates to an electric vehicle regenerative braking stability control method and system oriented to a non-standard road surface. The regenerative braking stability control method in the vehicle emergency braking scene comprises the steps that according to information obtained by a wheel speed sensor, in combination with vehicle parameters and the vehicle speed, processing is conducted through a dynamic model, and the relation between the current slip rate and the optimal slip rate is obtained. And inputting the identified slip rate at the peak attachment state moment as a control reference quantity into a model prediction controller, solving a torque required by motor braking in the controller, inputting the torque into a motor control unit, and performing regenerative braking through an electric driving system. On the basis of identifying the slip rate, the method gets rid of the problem of dependence on a tire model existing in most response-based methods, does not need to consider a tire ground model, damping rigidity and other difficult-to-obtain quantities, is not limited by various information acquired by multiple sensors, and is high in accuracy. And the applicability of the method under different working conditions is improved while the identification method is simplified.