WO2022183808A1 - 一种智能交通环境下的线控底盘信息物理***及控制方法 - Google Patents

一种智能交通环境下的线控底盘信息物理***及控制方法 Download PDF

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Publication number
WO2022183808A1
WO2022183808A1 PCT/CN2021/138518 CN2021138518W WO2022183808A1 WO 2022183808 A1 WO2022183808 A1 WO 2022183808A1 CN 2021138518 W CN2021138518 W CN 2021138518W WO 2022183808 A1 WO2022183808 A1 WO 2022183808A1
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Prior art keywords
driving
driver
information
steering
vehicle
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PCT/CN2021/138518
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English (en)
French (fr)
Inventor
赵万忠
***
王春燕
栾众楷
张自宇
钟怡欣
章波
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南京航空航天大学
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Priority to JP2022562549A priority Critical patent/JP2023522657A/ja
Priority to US17/924,995 priority patent/US11858525B2/en
Publication of WO2022183808A1 publication Critical patent/WO2022183808A1/zh

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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W10/00—Conjoint control of vehicle sub-units of different type or different function
    • B60W10/20—Conjoint control of vehicle sub-units of different type or different function including control of steering systems
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
    • B60W50/08—Interaction between the driver and the control system
    • B60W50/12—Limiting control by the driver depending on vehicle state, e.g. interlocking means for the control input for preventing unsafe operation
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W10/00—Conjoint control of vehicle sub-units of different type or different function
    • B60W10/04—Conjoint control of vehicle sub-units of different type or different function including control of propulsion units
    • B60W10/08—Conjoint control of vehicle sub-units of different type or different function including control of propulsion units including control of electric propulsion units, e.g. motors or generators
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W10/00—Conjoint control of vehicle sub-units of different type or different function
    • B60W10/18—Conjoint control of vehicle sub-units of different type or different function including control of braking systems
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
    • B60W40/08—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to drivers or passengers
    • B60W40/09—Driving style or behaviour
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
    • B60W40/10—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to vehicle motion
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
    • B60W50/08—Interaction between the driver and the control system
    • B60W50/10—Interpretation of driver requests or demands
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
    • B60W2050/0001—Details of the control system
    • B60W2050/0043—Signal treatments, identification of variables or parameters, parameter estimation or state estimation
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2510/00—Input parameters relating to a particular sub-units
    • B60W2510/06—Combustion engines, Gas turbines
    • B60W2510/0604—Throttle position
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2510/00—Input parameters relating to a particular sub-units
    • B60W2510/18—Braking system
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2510/00—Input parameters relating to a particular sub-units
    • B60W2510/20—Steering systems
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2510/00—Input parameters relating to a particular sub-units
    • B60W2510/20—Steering systems
    • B60W2510/202—Steering torque
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2540/00—Input parameters relating to occupants
    • B60W2540/10—Accelerator pedal position
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2540/00—Input parameters relating to occupants
    • B60W2540/12—Brake pedal position
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2540/00—Input parameters relating to occupants
    • B60W2540/18—Steering angle
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2554/00—Input parameters relating to objects
    • B60W2554/40—Dynamic objects, e.g. animals, windblown objects
    • B60W2554/404—Characteristics
    • B60W2554/4041—Position
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2554/00—Input parameters relating to objects
    • B60W2554/80—Spatial relation or speed relative to objects
    • B60W2554/802—Longitudinal distance
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2556/00—Input parameters relating to data
    • B60W2556/45—External transmission of data to or from the vehicle
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2556/00—Input parameters relating to data
    • B60W2556/45—External transmission of data to or from the vehicle
    • B60W2556/65—Data transmitted between vehicles
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
    • Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
    • Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]

Definitions

  • the invention belongs to the technical field of vehicle chassis control, and specifically refers to a wire-controlled chassis information physical system and a control method in an intelligent traffic environment.
  • wire-controlled technology With the development of automobile intelligence, electrification, and electronics, wire-controlled technology has been widely used in automobiles. In the wire-controlled technology, there is no mechanical connection between the actuator and the operating mechanism, and there is no mechanical energy transmission.
  • the operating instructions of the driver are sensed by sensors and transmitted to the actuator and the electronic controller in the form of electrical signals through the Internet.
  • the actuators of traditional vehicle chassis control are mainly realized by complex mechanical or hydraulic systems, and the driver is still a key component of the control system. Due to various physical factors, various decisions made by the driver aiming at the safe driving of the vehicle will be affected to a certain extent, and the driving of the vehicle has certain hidden dangers.
  • the wire-controlled chassis collects driver operation information, vehicle driving information, traffic environment information, etc. through sensors, converts the collected information into electrical signals and transmits them to the electronic control unit to control the work of the actuator. Through the driver's intention, combined with real-time road conditions, the driver's driving decisions are adjusted and revised according to the real-time road conditions in an intelligent traffic environment, providing drivers with safe assisted driving.
  • the Chinese invention patent application number is CN201510882930.9, and the title is "a vehicle steering control device, control method and automobile", which proposes that the steering controller is connected with the rotation angle signal collector, and the wheel steering control signal is generated according to the steering wheel angle signal, and the steering drive motor The steering of the wheels will be controlled according to the wheel steering control signal, but since the steering of the steering wheel is still controlled by the driver, if the driver's operation deviates, there will be certain hidden dangers in the driving of the vehicle.
  • the Chinese patent application number is CN201810733593.0, and the title is "A method for identifying and controlling driver's driving intention". The driver's intention is preliminarily identified through the collected driver information, vehicle driving information and traffic environment information.
  • the purpose of the present invention is to provide a wire-controlled chassis cyber-physical system and control method in an intelligent traffic environment, so as to solve the problem that in the prior art, it is difficult to realize ideal driving through the driver's operational awareness and environmental information. operational problems.
  • a wire-controlled chassis cyber-physical system in an intelligent traffic environment comprising: SoS-level CPS, system-level CPS and unit-level CPS; data transmission between multiple unit-level CPS and one system-level CPS, multiple system-level CPS and Realize data transmission between a SoS-level CPS;
  • the unit-level CPS is a wire-controlled chassis, including: a driver input module, a basic control module, an execution module and an environment perception module;
  • the driver input module includes: accelerator pedal and its travel and force sensor, brake pedal and its travel and force sensor, steering wheel and its rotation angle and torque sensor, wheel angle sensor, used for sensing the driving of the driver to the vehicle input , braking, steering information, to achieve the extraction of the driver's operation intention;
  • the basic control module processes the data collected by each sensor, formulates an optimal driving strategy according to the current working condition, and transmits it to the execution module;
  • the execution module is configured to receive the optimal driving strategy of the above-mentioned basic control module, and control the vehicle;
  • the environment perception module includes: a detection device, a positioning device and a communication device; the detection device is used for sensing information outside the vehicle and information about road conditions ahead; the positioning device is used for locating the position of the vehicle; the communication device is used for the vehicle and the vehicle Communication between vehicles and between vehicles and base stations to obtain real-time working condition information during vehicle driving;
  • the system-level CPS is a supervision platform, including: collaborative control module, real-time monitoring and diagnosis module; it is used to supervise the driving behavior of vehicles with drive-by-wire chassis on the same road;
  • the cooperative control module is used to obtain the sensor data of the supervised wire-controlled chassis and the execution information sent by the execution module, obtain the local optimal solution under the current working condition through information exchange and real-time analysis, and issue a control signal to the basic control module;
  • the real-time monitoring and diagnosis module described above is used to monitor and diagnose the driving situation of the vehicle equipped with the drive-by-wire chassis;
  • SoS-level CPS is a big data platform, including: data storage unit, data interaction module, data analysis module, and data transmission with various supervision platforms through the Internet;
  • the data storage unit is used to store the data transmitted to the big data platform; the data interaction module is used to realize the transmission of sensor data and execution information between the wire-controlled chassis and the supervision platform; the data analysis module is used to analyze the transmission to Based on the data of the big data platform, the ideal operation of the wire-controlled chassis is obtained, and it is judged whether the driving operation of the wire-controlled chassis is an ideal operation.
  • the basic control module includes: a central control unit, a steering control unit, a braking control unit, and a driving control unit; the central control unit is used to monitor and control the steering control unit, the braking control unit and the driving control unit, Receive signals from various sensors for calculating vehicle speed and distributing steering, braking and driving forces.
  • the optimal driving strategy is the execution state of the execution module that conforms to the current operating conditions, and the optimal driving strategy includes: an optimal steering strategy, an optimal braking strategy, an optimal driving strategy, and an optimal composite driving strategy;
  • the optimal steering strategy, the optimal braking strategy, and the optimal driving strategy are formulated under the single operating conditions of steering, braking and driving respectively;
  • the optimal composite driving strategy is the optimal steering strategy and the optimal braking strategy or the optimal driving strategy.
  • the optimal steering strategy includes the minimum actual energy consumption of the steering execution motor, and the wheel angle does not need to be corrected by the driver;
  • the optimal braking strategy includes the minimum energy consumption of the brake motor and the shortest execution time of the brake actuator .
  • No driver correction is required during the execution of the brake actuator;
  • the optimal driving strategy includes the minimum energy consumption of the in-wheel motor, the shortest execution time of the drive actuator, and no driver correction during the execution of the drive actuator.
  • the execution module includes: wheels, hub motors, steering execution motors, steering controllers, steering shafts, transmission shafts, rack and pinion steering gears, steering rods, brake controllers, brake actuators, and brake motors , drive controller, drive actuator.
  • the information outside the vehicle includes information on road lane lines, road arrow signs, roadside traffic signs, and traffic lights.
  • the forward road condition information includes forward bumpy obstacles, vehicles, and pedestrians.
  • the local optimal solution is the driving behavior of all drive-by-wire chassis of the same supervision platform, including steering, braking, driving, steering and braking, and steering and driving.
  • the data transmitted to the big data platform includes: sensor data, execution information, vehicle external information, forward road condition information, location information, vehicle-to-vehicle communication information, vehicle-to-base station communication information, and local optimal generated by the supervision platform. Program.
  • the ideal operation of the wire-controlled chassis is the data in the ideal operation database, including the ideal steering wheel angle, the ideal brake pedal opening, and the ideal accelerator pedal opening;
  • the ideal steering wheel angle is required by the desired path planned by the data analysis module.
  • the ideal brake pedal opening is the brake pedal opening that is planned by the data analysis module to maintain a safe distance from the obstacles ahead and surrounding obstacles and ensure the driver's driving comfort;
  • the ideal accelerator pedal opening The accelerator pedal opening that is planned for the data analysis module to ensure the driver's driving comfort and maintain a safe distance from the surrounding obstacles in line with the speed requirements of the traffic environment.
  • the ideal operation database is an offline synchronization database, which is composed of vehicle engineer experience data, vehicle dynamics and kinematic model data, and offline synchronization of vehicle driving data in the traffic environment; the data in the ideal operation database are all in safe driving and ensure driving.
  • the range of driver comfort; the vehicle engineer experience data includes the driver's steering, braking, driving, steering and braking or driving conditions of driving comfort data, the driver's steering, braking, driving operating force and vehicle speed, acceleration
  • Non-linear mathematical model data includes the dynamics and kinematic equations of steering, braking, and driving execution calculated by Newton's laws of motion, and the steering, braking calculated by Kirchhoff's laws , the current equations of the steering execution motor, the braking motor, the driving motor, and the in-wheel motor during driving execution;
  • the vehicle driving data in the traffic environment is the driving information data stored by the networked wire-controlled chassis vehicle in the networked condition.
  • the steering connection relationship between the driver input module, the basic control module and the execution module is as follows: the steering wheel angle and the torque sensor are integrated with the steering wheel, the steering wheel is connected to the transmission shaft through the steering shaft, and the transmission shaft is connected to the rack and pinion. Steering gear, rack and pinion steering gear is connected with the steering rod; the steering execution motor is fixed on the drive shaft, when the steering wheel is turned, the angle and torque sensors work, and the steering controller will collect the steering wheel angle and torque, and transmit the information of the wheel angle to the steering
  • the control unit the steering control unit controls the current output of the steering execution motor according to the sensor information, and then controls the steering of the transmission shaft; the steering controller is connected with the hub motor to control the rotation of the four wheels.
  • the braking connection relationship between the driver input module, the basic control module and the execution module is as follows: when the brake pedal is stepped on, the stroke and force sensor of the brake pedal work, and the brake controller will collect braking information.
  • the pedal stroke and force sensor information is transmitted to the brake control unit, and the brake control unit controls the current output of the brake motor according to the sensor information, and then controls the execution state of the brake actuator to realize the braking of the vehicle; the brake controller It is connected with the hub motor to control the rotation state of the wheel when braking.
  • the driving connection relationship between the driver input module, the basic control module and the execution module is: when the accelerator pedal is stepped on, the stroke and force sensor of the accelerator pedal work, and the drive controller will collect the stroke and force of the accelerator pedal.
  • the sensor information is transmitted to the drive control unit, and the drive control unit controls the execution state of the drive actuator according to the sensor information to drive the vehicle; the drive controller is connected to the in-wheel motor of the wheel to control the rotation state of the wheel when it accelerates.
  • the wheel hub motors include: a left front wheel hub motor, a right front wheel hub motor, a left rear wheel hub motor, and a right rear wheel hub motor; the four wheel hub motors are respectively integrated in the corresponding four wheel hubs for drive the wheels.
  • the wire-controlled chassis, supervision platform, and big data platform complete data transmission through the Internet
  • the data transmission process is as follows: the drive-by-wire chassis obtains the driver's operation information and environmental information after the driver completes the driving operation, and transmits it to the supervision platform; the real-time monitoring and diagnosis module of the supervision platform transmits the driver's operation information to the drive-by-wire chassis.
  • the big data platform completes information storage and interaction, obtains the operation behavior information of the wire-controlled chassis through the data analysis module, and transmits it to the supervision platform; the collaborative control of the supervision platform
  • the module generates a local optimal plan according to the information transmitted by the big data platform and transmits it to the wire-controlled chassis; the basic control module of the wire-controlled chassis forms the optimal driving strategy according to the local optimal plan, and the execution module controls the vehicle according to the optimal driving strategy.
  • the present application also provides a control method of a wire-controlled chassis cyber-physical system in an intelligent traffic environment, the steps are as follows:
  • the basic control module judges the driver's operation according to the sensor information of the driver's input module, and transmits the driver's operation information and the information of the environment perception module to the supervision platform;
  • the supervision platform conducts real-time monitoring and diagnosis on the information of the wire-controlled chassis, and judges whether the current driver's operation conforms to the current working conditions; Platform; if it does not meet the working conditions, the supervision platform adjusts the driver's operation according to the information of the environmental perception module to meet the current working conditions, and transmits the information of the environmental perception module and the adjusted driver's operation information to the big data platform;
  • the big data platform stores the operation information transmitted by the supervision platform
  • the big data platform analyzes the driver's operation information transmitted by the supervision platform; if the analysis result of the driver's operation information in the supervision platform is an ideal driving operation, the driver's operation information is fed back to the supervision platform; if the driver's operation information is analyzed If there is an error between the result and the ideal driving operation information, the ideal driving operation information obtained by data analysis is fed back to the supervision platform;
  • the supervision platform forms a real-time local optimal solution for the vehicle according to the feedback information, and feeds back the local optimal solution to the wire-controlled chassis supervised by the current supervision platform;
  • the central control unit will generate the optimal driving strategy corresponding to the local optimal solution, and transmit it to the steering control unit, braking control unit, and drive control unit to control the output current of the motor in the execution module, so that the controller can control the execution Other actuators in the module are controlled to complete the output to the vehicle.
  • the operation signals sent by the driver in the step 1) include: steering, braking, driving, and compound operation signals, wherein the compound operation signal is a combination of steering and braking or driving.
  • the current steering wheel angle and torque, wheel angle, brake pedal stroke, and accelerator pedal stroke of the vehicle are obtained through sensors, and the current working condition is obtained through the detection equipment, positioning equipment and communication equipment in the environment perception module. information outside the vehicle, road conditions ahead, location information, vehicle-to-vehicle communication information, and vehicle-to-base station communication information.
  • the driver's operation in the step 3) includes steering, braking, driving, and compound operation, wherein the compound operation includes a combination of steering and braking or driving.
  • the supervisory platform of any road fails, the supervisory platform of any other road will take over the data information of the supervisory platform that has failed, and the corresponding road in the current road and the supervisory platform that has failed will be taken over by the supervisory platform of any other road. Real-time monitoring and diagnosis of the wire-controlled chassis to ensure the stability of traffic environment information.
  • the current working condition of the step 4) includes a steering working condition, a braking working condition, an acceleration working condition, a combined working condition of a steering working condition and a braking working condition or an acceleration working condition; Lane, overtaking, lane change; braking conditions include the vehicle in front decelerating and the distance from the vehicle in front is less than the traffic safety distance, emergency obstacle avoidance parking, and passing the speed limit section when the vehicle speed is higher than the speed limit; the acceleration conditions include vehicle starting, vehicle speed Pass the speed limit section and overtake when the speed limit section is lower than the speed limit section.
  • the central control unit controls the steering, braking, and driving control units to drive the wheel hub motor, the steering executive motor, and the brake motor to output additional control.
  • the control algorithm used is the H ⁇ feedback control algorithm, which specifically includes the following contents:
  • the deviations e 1 , e 2 , and e 3 are the inputs of the H ⁇ feedback controller K(s), and the feedback controller K(s ) calculates the steering execution motor, braking
  • Additional rotation angles ⁇ 1 , ⁇ 2 , ⁇ 3 are the inputs of the H ⁇ feedback controller K(s), and the feedback controller K(s ) calculates the steering execution motor, braking
  • the motor includes a steering executive motor, a braking motor, and a wheel hub motor;
  • the controller includes a steering controller, a braking controller, and a drive controller;
  • the other executive mechanisms are the executive modules in addition to the executive motor, the system is controlled. Electric motor, wheel hub motor, steering controller, brake controller, actuator of the drive controller.
  • the invention integrates the in-wheel motor and the suspension, cancels the traditional structures such as the engine and the clutch, simplifies the structure of the chassis, and the motor can directly drive the vehicle to run, and applies different driving, braking or rotation to different wheels through the four in-wheel motors.
  • the torque meets the independent control of the wheels, which improves active safety and operational stability.
  • the invention integrates the intelligent traffic environment, takes the wire-controlled chassis as an integral part of the cyber-physical system, integrates information technologies and automatic control technologies such as perception, computing, communication, control, etc. Elements such as environment and information constitute a closed loop of "perception-analysis-decision-execution" of intelligent vehicles.
  • the invention obtains the driver's intention and environmental information through the sensors and detection and positioning communication equipment of the wire-controlled chassis, obtains the information of the road vehicles through the cyber-physical system, obtains more real-time traffic condition information based on the intelligent traffic environment, and improves the traditional
  • the technology's information acquisition for vehicle safety control is only based on the driving information read by the vehicle's sensors and the surrounding real-time working condition information obtained by laser and radar, and the lack of reading the driving behavior information of other vehicles on the road is insufficient.
  • the invention can analyze the ideal driving operation action of the vehicle under the current working condition, the central control unit of the wire-controlled chassis obtains the optimal driving strategy according to the ideal driving operation, and the wire-controlled chassis will diagnose the driver's intention according to the analysis result of the supervision platform, and The error of steering or braking is corrected, and the safety of the vehicle is improved through the control of each module of the wire-controlled chassis.
  • the driver monitoring system only issues a warning to the driver when the driver misoperation, and in severe cases, the vehicle is forced to slow down or lock the vehicle.
  • the supervision platform in the wire-controlled chassis cyber-physical system of the present invention can communicate, interconnect and interoperate with the support of the big data platform, and through the wire-controlled chassis cyber-physical system, the information of all vehicles on the road can be monitored, diagnosed and data analyzed. , which improves the accuracy of traffic environment prediction.
  • the other supervision platforms can take over the faulty supervision platform in time to ensure the stability of the input of intelligent traffic environment information.
  • FIG. 1 is a schematic structural diagram of a wire-controlled chassis cyber-physical system according to an embodiment of the present application.
  • FIG. 2 is a structural diagram of a wire-controlled chassis according to an embodiment of the present application.
  • FIG. 3 is a flow chart of the specific implementation of the method according to the embodiment of the present application.
  • FIG. 4 is a structural diagram of the H ⁇ feedback control of the embodiment.
  • a wire-controlled chassis cyber-physical system in an intelligent traffic environment of the present invention includes: SoS-level CPS, system-level CPS and unit-level CPS; through the network, multiple unit-level CPS and a system-level CPS Realize data transmission between multiple system-level CPS and one SoS-level CPS;
  • the unit-level CPS is a wire-controlled chassis, as shown in Figure 2, including: a driver input module, a basic control module, an execution module and an environment perception module;
  • the driver input module includes: accelerator pedal and its travel and force sensor, brake pedal and its travel and force sensor, steering wheel and its rotation angle and torque sensor, wheel angle sensor, used for sensing the driving of the driver to the vehicle input , braking, steering information, to achieve the extraction of the driver's operation intention;
  • the basic control module processes the data collected by each sensor, formulates an optimal driving strategy according to the current working condition, and transmits it to the execution module;
  • the execution module is configured to receive the optimal driving strategy of the above-mentioned basic control module, and control the vehicle;
  • the execution module includes: wheel, hub motor, steering execution motor, steering controller, steering shaft, transmission shaft, rack and pinion steering gear, steering rod, brake controller, brake actuator, brake motor, Drive controller, drive actuator.
  • the optimal driving strategy is the execution state of the execution module that conforms to the current operating conditions, and the optimal driving strategy includes: an optimal steering strategy, an optimal braking strategy, an optimal driving strategy, and an optimal composite driving strategy; the The optimal steering strategy, the optimal braking strategy and the optimal driving strategy are formulated under the single operating conditions of steering, braking and driving respectively; the optimal composite driving strategy is the optimal steering strategy and the optimal braking strategy or the optimal driving strategy.
  • the optimal steering strategy includes the minimum actual energy consumption of the steering execution motor, and the wheel angle does not require driver correction
  • the optimal braking strategy includes the minimum energy consumption of the brake motor, the shortest execution time of the brake actuator, No driver correction is required during the execution of the brake actuator
  • the optimal driving strategy includes the minimum energy consumption of the in-wheel motor, the shortest execution time of the drive actuator, and no driver correction during the execution of the drive actuator.
  • the environment perception module includes: a detection device, a positioning device and a communication device; the detection device is used for sensing information outside the vehicle and information about road conditions ahead; the positioning device is used for locating the position of the vehicle; the communication device is used for the vehicle and the vehicle Communication between vehicles and between vehicles and base stations to obtain real-time working condition information during vehicle driving;
  • the basic control module includes: a central control unit, a steering control unit, a braking control unit, and a driving control unit; the central control unit is used to monitor and control the steering control unit, the braking control unit and the driving control unit, and receives The signals of each sensor are used to calculate the speed of the vehicle and distribute the steering, braking and driving forces.
  • the system-level CPS is a supervision platform, including: collaborative control module, real-time monitoring and diagnosis module; it is used to supervise the driving behavior of vehicles with drive-by-wire chassis on the same road;
  • the cooperative control module is used to obtain the sensor data of the supervised wire-controlled chassis and the execution information sent by the execution module, obtain the local optimal solution under the current working condition through information exchange and real-time analysis, and issue a control signal to the basic control module;
  • the real-time monitoring and diagnosis module described above is used to monitor and diagnose the driving situation of the vehicle equipped with the drive-by-wire chassis;
  • SoS-level CPS is a big data platform, including: data storage unit, data interaction module, data analysis module, and data transmission with various supervision platforms through the Internet;
  • the data storage unit is used to store the data transmitted to the big data platform;
  • the data interaction module is used to realize the transmission of sensor data and execution information between the wire-controlled chassis and the supervision platform;
  • the data analysis module is used to analyze the transmission to Based on the data of the big data platform, the ideal operation of the wire-controlled chassis is obtained, and whether the driving operation of the wire-controlled chassis is an ideal operation;
  • the information outside the vehicle includes information on road lane lines, road arrow signs, roadside traffic signs, and traffic lights.
  • the forward road condition information includes forward bumpy obstacles, vehicles, and pedestrians.
  • the local optimal solution is the driving behavior of all drive-by-wire chassis of the same supervisory platform, including steering, braking, driving, steering and braking, and steering and driving.
  • the data transmitted to the big data platform includes: sensor data, execution information, vehicle external information, forward road condition information, location information, vehicle-to-vehicle communication information, vehicle-to-base station communication information, and local optimal solutions generated by the supervision platform.
  • the ideal operation of the wire-controlled chassis is the data in the ideal operation database, including the ideal steering wheel angle, the ideal brake pedal opening, and the ideal accelerator pedal opening;
  • the ideal steering wheel angle is the steering wheel angle required by the desired path planned by the data analysis module size;
  • the ideal brake pedal opening is the brake pedal opening that is planned by the data analysis module to maintain a safe distance from the obstacles ahead and surrounding obstacles and ensure the driver's driving comfort;
  • the ideal accelerator pedal opening is the data analysis module The module plans the accelerator pedal opening that meets the speed requirements of the traffic environment to ensure the driver's driving comfort and maintain a safe distance from the surrounding obstacles.
  • the ideal operation database is an offline synchronization database, which is composed of vehicle engineer experience data, vehicle dynamics and kinematic model data, and vehicle driving data in the traffic environment.
  • the vehicle engineer experience data includes the driver's steering, braking, driving, steering and braking or driving conditions driving comfort data, the driver's steering, braking, driving operating force and vehicle speed, acceleration nonlinear mathematics Model data
  • the vehicle dynamics and kinematics model includes the dynamics and kinematic equations when steering, braking, and driving are performed by Newton's laws of motion, and the steering, braking, and driving are performed by Kirchhoff's laws.
  • the vehicle driving data in the traffic environment is the driving information data stored by the networked wire-controlled chassis vehicle in the networked condition.
  • the steering connection relationship between the driver input module, the basic control module and the execution module is as follows: the steering wheel angle and the torque sensor are integrated with the steering wheel, the steering wheel is connected to the transmission shaft through the steering shaft, and the transmission shaft is connected to the rack and pinion.
  • Steering gear, rack and pinion steering gear is connected with the steering rod;
  • the steering execution motor is fixed on the drive shaft, when the steering wheel is turned, the angle and torque sensors work, and the steering controller will collect the steering wheel angle and torque, and transmit the information of the wheel angle to the steering
  • the control unit the steering control unit controls the current output of the steering execution motor according to the sensor information, and then controls the steering of the transmission shaft;
  • the steering controller is connected with the hub motor to control the rotation of the four wheels.
  • the brake connection relationship between the driver input module, the basic control module, and the execution module is: when the brake pedal is depressed, the stroke of the brake pedal and the force sensor work, and the brake controller will collect the stroke of the brake pedal. and force sensor information is sent to the brake control unit, the brake control unit controls the current output of the brake motor according to the sensor information, and then controls the execution state of the brake actuator to realize the braking of the vehicle; the brake controller and the wheel hub motor Connect to control the rotation state of the wheel when braking.
  • the driving connection relationship between the driver input module, the basic control module, and the execution module is: when the accelerator pedal is stepped on, the accelerator pedal stroke and force sensor work, and the drive controller will collect the accelerator pedal stroke and force sensor information transmission.
  • the drive control unit controls the execution state of the drive actuator according to the sensor information to realize the drive of the vehicle; the drive controller is connected to the in-wheel motor of the wheel to control the rotation state of the wheel when it is accelerated.
  • the wheel hub motors include: left front wheel hub motors, right front wheel hub motors, left rear wheel hub motors, right rear wheel hub motors; four wheel hub motors are respectively integrated in the corresponding four wheel hubs for driving the wheels.
  • the wire-controlled chassis, supervision platform, and big data platform complete data transmission through the Internet
  • the data transmission process is as follows: the drive-by-wire chassis obtains the driver's operation information and environmental information after the driver completes the driving operation, and transmits it to the supervision platform; the real-time monitoring and diagnosis module of the supervision platform transmits the driver's operation information to the drive-by-wire chassis.
  • the big data platform completes information storage and interaction, obtains the operation behavior information of the wire-controlled chassis through the data analysis module, and transmits it to the supervision platform; the collaborative control of the supervision platform
  • the module generates a local optimal plan according to the information transmitted by the big data platform and transmits it to the wire-controlled chassis; the basic control module of the wire-controlled chassis forms the optimal driving strategy according to the local optimal plan, and the execution module controls the vehicle according to the optimal driving strategy.
  • the present embodiment also provides a control method of a wire-controlled chassis cyber-physical system based on the above-mentioned system in an intelligent traffic environment.
  • the specific steps are as follows:
  • the driver sends an operation signal;
  • the operation signal sent by the driver includes: steering, braking, driving, and compound operation signals, wherein the compound operation signal is a combination of steering and braking or driving.
  • the current steering wheel angle and torque, wheel angle, brake pedal stroke, and accelerator pedal stroke of the vehicle are obtained through the sensor, and the outside of the vehicle under the current working condition is obtained through the detection equipment, positioning equipment and communication equipment in the environment perception module. information, road conditions ahead, location information, vehicle-to-vehicle communication information, and vehicle-to-base station communication information.
  • the basic control module judges the driver's operation according to the sensor information of the driver's input module, and transmits the driver's operation information and the information of the environment perception module to the supervision platform; the driver's operation includes steering, braking, driving, and compound operations, among which Compound operations include the combination of steering and braking or actuation.
  • the supervision platform conducts real-time monitoring and diagnosis of the information of the wire-controlled chassis through the network, and judges whether the current driver's operation conforms to the current working conditions; Big data platform; if it does not meet the working conditions, the supervision platform adjusts the driver's operation according to the information of the environmental perception module to meet the current working conditions, and transmits the information of the environmental perception module and the adjusted driver's operation information to the big data platform;
  • the supervision platform of any road fails, the supervision platform of any other road will take over the data information of the supervision platform that has failed, and the wire control of the road corresponding to the supervision platform in the current road and the faulty supervision platform will be taken over by the supervision platform of any other road.
  • Real-time monitoring and diagnosis of the chassis to ensure the stability of traffic environment information;
  • the current working conditions of the step 4) include steering working conditions, braking working conditions, acceleration working conditions, and combined working conditions of steering working conditions and braking working conditions or acceleration working conditions; wherein the steering working conditions include passing through curves, overtaking , changing lanes; braking conditions include the vehicle in front decelerating and the distance from the vehicle in front is less than the traffic safety distance, emergency obstacle avoidance parking, and passing the speed limit road section when the vehicle speed is higher than the speed limit; the acceleration conditions include the vehicle starting, the vehicle speed lower than the limit Passing the speed limit section and overtaking in the speed section;
  • the big data platform stores the operation information transmitted by the supervision platform
  • the big data platform analyzes the driver's operation information transmitted by the supervision platform; if the analysis result of the driver's operation information in the supervision platform is an ideal driving operation, the driver's operation information is fed back to the supervision platform; if the driver's operation information is analyzed If there is an error between the result and the ideal driving operation information, the ideal driving operation information obtained by data analysis is fed back to the supervision platform;
  • the central control unit controls the steering, braking, and driving control units to drive the wheel hub motor, the steering execution motor, and the brake motor to output additional control quantities to output additional control quantities.
  • the control algorithm used is the H ⁇ feedback control algorithm, as shown in Figure 4, including the following:
  • the deviations e 1 , e 2 , and e 3 are the inputs of the H ⁇ feedback controller K(s), and the feedback controller K(s ) calculates the steering execution motor, braking
  • Additional rotation angles ⁇ 1 , ⁇ 2 , ⁇ 3 are the inputs of the H ⁇ feedback controller K(s), and the feedback controller K(s ) calculates the steering execution motor, braking
  • the supervision platform forms a real-time local optimal solution for the vehicle according to the feedback information, and feeds back the local optimal solution to the wire-controlled chassis supervised by the current supervision platform through the Internet;
  • the central control unit will generate the optimal driving strategy corresponding to the local optimal solution, and transmit it to the steering control unit, braking control unit, and drive control unit to control the output current of the motor in the execution module, so that the controller can control the execution Other actuators in the module are controlled to complete the output to the vehicle;
  • the motor includes a steering executive motor, a braking motor, and a wheel hub motor;
  • the controller includes a steering controller, a braking controller, and a driving controller;
  • the other executive mechanisms are in the executive module, except for the executive motor and the braking motor, In-wheel motor, steering controller, brake controller, actuator of drive controller.

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Abstract

一种智能交通环境下的线控底盘信息物理***及控制方法，该***包括：SoS级CPS、***级CPS和单元级CPS；多个单元级CPS与一个***级CPS之间实现数据传输，多个***级CPS与一个SOS级CPS之间实现数据传输；该***将轮毂电机与悬架进行集成，取消发动机、离合器等传统结构，简化了底盘的结构，电机直接驱动车辆运转，并通过四个轮毂电机对不同车轮施加不同驱动、制动或转矩满足车轮的独立控制，提高了主动安全性和操作稳定性。

Description

一种智能交通环境下的线控底盘信息物理***及控制方法 技术领域
本发明属于车辆底盘控制技术领域，具体指代一种智能交通环境下的线控底盘信息物理***及控制方法。
背景技术
随着汽车智能化、电动化、电子化的发展，线控技术在汽车上得到普遍的应用。线控技术中执行机构和操作机构两者没有机械联结也没有机械能量的传递，汽车驾驶员的操作指令通过传感器感知，采用电信号的形式通过互联网传递给执行机构与电子控制器。
传统汽车底盘控制的执行机构主要靠复杂的机械或液压***实现，驾驶员仍是控制***的关键组成部分。由于各种物理因素，驾驶员作出的以车辆安全行驶为目标的各种决策会受到一定的影响，车辆的行驶存在一定的安全隐患。线控底盘则通过传感器采集驾驶员操作信息、车辆行驶信息、交通环境信息等，将采集的信息转换为电信号通过传递给电子控制单元，进而控制执行机构工作。通过驾驶员意图，结合实时路况，在智能交通环境下根据实时路况对驾驶员的驾驶决策进行调整和修正，为驾驶员提供安全的辅助驾驶。
中国发明专利申请号为CN201510882930.9，名称为“一种车辆转向控制装置、控制方法及汽车”中提出转向控制器与转角信号采集器连接，根据方向盘转角信号生成车轮转向控制信号，转向驱动电机将根据车轮转向控制信号控制车轮的转向，但由于方向盘转向仍由驾驶员控制，若驾驶员操作出现偏差，则车辆的行驶存在一定隐患。中国专利发明申请号为CN201810733593.0，名称为“一种驾驶员驾驶意图识别及控制方法”中通过采集的驾驶员信息、车辆行驶信息和交通环境信息初步识别驾驶员意图，根据驾驶员初步的意图改变车辆行驶状态，再根据驾驶员调整的操作以及车辆的行驶数据，进一步识别驾驶员意图，该专利只对驾驶员操作意识进行识别，未通过车辆行驶信息和交通环境信息对驾驶员操作行为进行修正，驾驶员的操作仍关系到驾驶的安全性。
发明内容
针对于上述现有技术的不足，本发明的目的在于提供一种智能交通环境下的线控底盘信息物理***及控制方法，以解决现有技术中难以通过驾驶员操作意识和环境信息实现理想驾驶操作的问题。
为达到上述目的，本发明采用的技术方案如下：
一种智能交通环境下的线控底盘信息物理***，包括：SoS级CPS、***级CPS和单元级CPS；多个单元级CPS与一个***级CPS之间实现数据传输，多个***级CPS与一个SoS级CPS之间实现数据传输；
所述单元级CPS为线控底盘，包括：驾驶员输入模块、基本控制模块、执行模块和环境感知模块；
所述驾驶员输入模块包括：油门踏板及其行程和力传感器、制动踏板及其行程和力传感器、方向盘及其转角和转矩传感器、车轮转角传感器，用于感知驾驶员对车辆输入的驱动、制动、转向信息，实现驾驶员操作意图的提取；
所述基本控制模块对各传感器采集的数据进行处理，根据当前工况制定最优行驶策略，并传递给执行模块；
所述执行模块用于接收上述基本控制模块的最优行驶策略，并对车辆进行操控；
所述环境感知模块，包括：探测设备、定位设备和通信设备；所述探测设备用于感知车辆外部的信息和前方路况信息；定位设备用于对车辆位置进行定位；通信设备用于车辆与车辆之间通讯、车辆与基站之间通讯，以获取车辆行驶过程中实时工况信息；
***级CPS为监管平台，包括：协同控制模块、实时监控和诊断模块；用于监管同一道路上装载线控底盘的车辆的驾驶行为；
所述协同控制模块用于获取监管的线控底盘的传感器数据和执行模块发出的执行信息，通过信息交互和实时分析获得当前工况下的局部最优方案，对基本控制模块发出控制信号；所述实时监控和诊断模块用于监控和诊断装载线控底盘的车辆的驾驶情况；
SoS级CPS为大数据平台，包括：数据存储单元、数据交互模块、数据分析模块，并通过互联网与各监管平台进行数据传输；
所述数据存储单元用于存储传输至大数据平台的数据；所述数据交互模块用于实现线控底盘、监管平台之间传感器数据、执行信息的传输；所述数据分析模块用于分析传输至大数据平台的数据，得出线控底盘理想操作，并判断线控底盘的驾驶操作是否为理想操作。
进一步地，所述基本控制模块包括：中央控制单元、转向控制单元、制动控制单元、驱动控制单元；所述中央控制单元用于监测和控制转向控制单元、制动控制单元和驱动控制单元，接收各传感器信号，用于计算车速，分配转向、制动和驱动力。
进一步地，所述最优行驶策略为符合当前工况的执行模块的执行状态，最优行驶策略包括：最优转向策略、最优制动策略、最优驱动策略、最优复合行驶策略；所述最优 转向策略、最优制动策略、最优驱动策略分别在转向、制动、驱动单一工况下制定；所述最优复合行驶策略为最优转向策略与最优制动策略或最优驱动策略的组合；所述最优转向策略包括转向执行电机实际能耗最小、车轮转角无需驾驶员修正；所述最优制动策略包括制动电机能耗最小、制动执行机构执行时间最短、制动执行机构执行过程中无需驾驶员修正；所述最优驱动策略包括轮毂电机能耗最小且驱动执行机构执行时间最短、驱动执行机构执行过程中无需驾驶员修正。
进一步地，所述执行模块包括：车轮、轮毂电机、转向执行电机、转向控制器、转向轴、传动轴、齿轮齿条转向器、转向拉杆、制动控制器、制动执行机构、制动电机、驱动控制器、驱动执行机构。
进一步地，所述车辆外部的信息包括：道路车道线、路面箭头标志、路旁交通标志牌、交通红绿灯的信息。
进一步地，所述前方路况信息包括前方的凹凸障碍物、车辆、行人。
进一步地，所述局部最优方案为同一监管平台的所有线控底盘的行驶行为，包括转向、制动、驱动、转向且制动、转向且驱动。
进一步地，所述传输至大数据平台的数据包括：传感器数据、执行信息、车辆外部信息、前方路况信息、位置信息、车辆与车辆通讯信息、车辆与基站通讯信息、监管平台生成的局部最优方案。
进一步地，所述线控底盘理想操作为理想操作数据库中数据，包括理想方向盘转角、理想制动踏板开度、理想加速踏板开度；所述理想方向盘转角为数据分析模块规划的期望路径所需的方向盘转角大小；所述理想制动踏板开度为数据分析模块规划的与前方和周围障碍物保持交通安全距离且保证驾驶员驾驶舒适度的制动踏板开度；所述理想加速踏板开度为数据分析模块规划的保证驾驶员驾驶舒适度且与周围障碍物保持交通安全距离的符合交通环境速度要求的加速踏板开度。
进一步地，所述理想操作数据库为离线同步数据库，由车辆工程师经验数据、汽车动力学和运动学模型数据、交通环境中汽车行驶数据离线同步组成；理想操作数据库中数据均处于安全驾驶且保证驾驶员舒适度范围；所述车辆工程师经验数据包括驾驶员转向、制动、驱动、转向与制动或驱动情况下驾驶舒适度数据，驾驶员转向、制动、驱动的操作力与车速、加速度的非线性数学模型数据；所述汽车动力学和运动学模型包括由牛顿运动定律计算的转向、制动、驱动执行时的动力学和运动学方程，由基尔霍夫定律计算的转向、制动、驱动执行时的转向执行电机、制动电机、驱动电机、轮毂电机的电 流方程；所述交通环境中汽车行驶数据为联网线控底盘汽车在联网情况下储存的驾驶信息数据。进一步地，所述驾驶员输入模块、基本控制模块、执行模块之间的转向连接关系为：方向盘转角和转矩传感器集成于与方向盘，方向盘通过转向轴与传动轴连接，传动轴连接齿轮齿条转向器，齿轮齿条转向器与转向拉杆连接；转向执行电机固定在传动轴上，当方向盘转动时转角和转矩传感器工作，转向控制器将采集方向盘转角和转矩、车轮转角信息传送至转向控制单元，转向控制单元根据传感器信息控制转向执行电机的电流输出，进而控制传动轴的转向；转向控制器与轮毂电机连接，控制四个车轮的转动。
进一步地，所述驾驶员输入模块、基本控制模块、执行模块之间的制动连接关系为：踩下制动踏板时，制动踏板的行程和力传感器工作，制动控制器将采集制动踏板的行程和力传感器信息传送至制动控制单元，制动控制单元根据传感器信息控制制动电机的电流输出，进而控制制动执行机构的执行状态，实现对车辆的制动；制动控制器与轮毂电机连接，控制车轮制动时的转动状态。
进一步地，所述驾驶员输入模块、基本控制模块、执行模块之间的驱动连接关系为：踩下油门踏板时，油门踏板的行程和力传感器工作，驱动控制器将采集油门踏板的行程和力传感器信息传送至驱动控制单元，驱动控制单元根据传感器信息控制驱动执行机构的执行状态，实现对车辆的驱动；驱动控制器与车轮的轮毂电机连接，控制车轮加速时的转动状态。
进一步地，所述轮毂电机包括：左前轮轮毂电机、右前轮轮毂电机、左后轮轮毂电机、右后轮轮毂电机；四个轮毂电机分别集成在相应的四个车轮轮毂中，用于驱动车轮。
线控底盘、监管平台、大数据平台通过互联网完成数据传输；
所述数据传输过程为：线控底盘在驾驶员完成驾驶操作后获取驾驶员操作信息和环境信息，并传输至监管平台；监管平台的实时监控和诊断模块对线控底盘传输的驾驶员操作信息和环境信息进行实时监控和诊断，将诊断结果传输至大数据平台；大数据平台完成信息存储和交互，通过数据分析模块获得线控底盘的操作行为信息，传输至监管平台；监管平台的协同控制模块根据大数据平台传输的信息生成局部最优方案，传输至线控底盘；线控底盘的基本控制模块根据局部最优方案形成最优行驶策略，执行模块根据最优行驶策略对车辆进行控制。
其次，本申请还提供了一种智能交通环境下的线控底盘信息物理***的控制方法，步骤如下：
1)驾驶员发出操作信号；
2)获取线控底盘的环境感知模块的信息和驾驶员输入模块的传感器信息；
3)基本控制模块根据驾驶员输入模块的传感器信息判断驾驶员的操作，将驾驶员操作信息和环境感知模块的信息传输至监管平台；
4)监管平台对线控底盘的信息进行实时监控和诊断，判断当前驾驶员的操作是否符合当前工况；若符合工况将监管平台获取的驾驶员操作和环境感知模块的信息传送至大数据平台；若不符合工况，监管平台根据环境感知模块的信息调整驾驶员操作以符合当前工况，将环境感知模块的信息和调整后的驾驶员操作信息传送至大数据平台；
5)大数据平台对监管平台传送的操作信息进行存储；
6)大数据平台对监管平台传送的驾驶员操作信息进行分析；若监管平台中的驾驶员操作信息分析结果为理想驾驶操作，则将驾驶员操作信息反馈至监管平台；若驾驶员操作信息分析结果与理想驾驶操作信息存在误差，则将数据分析得到的理想驾驶操作信息反馈至监管平台；
7)监管平台根据反馈信息形成车辆实时的局部最优方案，将局部最优方案反馈给当前监管平台所监管的线控底盘；
8)中央控制单元将生成对应局部最优方案的最优行驶策略，并传递给转向控制单元、制动控制单元、驱动控制单元，来控制执行模块中电机的输出电流，从而使控制器对执行模块中其他执行机构进行控制，完成对车辆的输出。
进一步地，所述步骤1)中驾驶员发出的操作信号包括：转向、制动、驱动、复合操作信号，其中复合操作信号为转向与制动或驱动的组合。
进一步地，所述步骤2)中通过传感器获取车辆当前方向盘转角和转矩、车轮转角、制动踏板行程、油门踏板行程，通过环境感知模块中的探测设备、定位设备和通讯设备获取当前工况下车辆外部的信息、前方路况信息、位置信息、车辆与车辆之间通讯信息、车辆与基站之间通讯信息。
进一步地，所述步骤3)中驾驶员操作包括转向、制动、驱动、复合操作，其中复合操作包括转向与制动或驱动的组合。
进一步地，所述步骤4)中若任一道路的监管平台出现故障，则由其他任一道路的监管平台接管出现故障的监管平台的数据信息，对当前道路内及出现故障的监管平台对应道路的线控底盘进行实时监控和诊断，保证交通环境信息的稳定。
进一步地，所述步骤4)的当前工况包括转向工况、制动工况、加速工况、转向工况与制动工况或加速工况的组合工况；其中转向工况包括通过弯道、超车、变道；制动 工况包括前方车辆减速且与前方车辆距离小于交通安全距离、紧急避障停车、车速高于限速时通过限速路段；其中加速工况包括车辆起步、车速低于限速路段时通过限速路段、超车。
进一步地，所述步骤6)中当前驾驶员的操作与理想驾驶操作存在误差，则由中央控制单元控制转向、制动、驱动控制单元以驱动轮毂电机、转向执行电机、制动电机输出附加控制量，以最小化驾驶员的操作与理想驾驶操作的误差；其中所利用的控制算法为H∞反馈控制算法，具体包括以下内容：
61)驾驶员输出的方向盘转角θ sw和理想方向盘转角
Figure PCTCN2021138518-appb-000001
的偏差表示为e 1；驾驶员输出的制动踏板开度p和理想制动踏板开度p *的偏差表示为e 2；驾驶员输出的加速踏板开度q和理想加速踏板开度q *的偏差表示为e 3；
62)偏差e 1，e 2，e 3为H∞反馈控制器K(s)的输入，反馈控制器K(s)根据输入偏差e 1，e 2，e 3计算出转向执行电机、制动电机和轮毂电机需要输出的附加转角θ 1，θ 2，θ 3，则中央控制单元和转向控制单元、制动控制单元、驱动控制单元分别控制转向执行电机、制动电机、轮毂电机输出相应的附加转角θ 1，θ 2，θ 3；
63)附加转角θ 1，θ 2，θ 3作用到线控底盘***，进而影响车辆的行驶状态，同时驾驶员根据当前车辆状态进行相应地驾驶操作，则得到一组新的偏差e 4，e 5，e 6；
64)重复步骤61)—63)，直至偏差e i(i＝1,2,3,...)消除。
进一步地，所述步骤8)中电机包括转向执行电机，制动电机，轮毂电机；控制器包括转向控制器，制动控制器，驱动控制器；其他执行机构为执行模块中除执行电机，制动电机，轮毂电机，转向控制器，制动控制器，驱动控制器的执行机构。
本发明的有益效果：
本发明将轮毂电机与悬架进行集成，取消发动机、离合器等传统结构，简化了底盘的结构，并且电机可直接驱动车辆运转，并通过四个轮毂电机对不同车轮施加不同驱动、制动或转矩满足车轮的独立控制，提高了主动安全性和操作稳定性。
本发明融合智能交通环境，将线控底盘作为信息物理***的组成部分，集成感知、计算、通信、控制等信息技术和自动控制技术，同时能够结合物理空间和信息空间中人、机、物、环境、信息等要素，构成智能车辆“感知-分析-决策-执行”的闭环。
本发明通过线控底盘的传感器和探测、定位通信设备获得驾驶员意图以及环境信息，通过信息物理***获取道路行驶车辆的信息，基于智能交通环境获取更多的实时交通工况信息，改善了传统技术对车辆的安全控制的信息获取只基于本车传感器读取的驾驶信息及激光、雷达获取的周围实时工况信息，缺少对路面其他车辆驾驶行为信息的读取的不足。
本发明能够分析当前工况下车辆的理想驾驶操作动作，线控底盘的中央控制单元根据理想驾驶操作得到最优行驶策略，线控底盘将根据监管平台的分析结果对驾驶员意图进行诊断，并进行转向或制动的误差进行修正，通过线控底盘各模块的控制，提高了车辆行驶的安全性。改善了现有技术中驾驶员误操作时，驾驶员监控***只对驾驶员发出警示，严重时对车辆进行强制降速或锁车的不足。
本发明线控底盘信息物理***中的监管平台在大数据平台的支持下能够互通、互联、互操作，通过线控底盘信息物理***可以将路面上所有行驶车辆的信息进行监控、诊断和数据分析，提高了交通环境预测的准确性。此外，若其中一个监管平台存在故障，其他监管平台能够及时接管该故障监管平台，保证智能交通环境信息输入的稳定。
附图说明
图1为本申请实施例线控底盘信息物理***结构示意图。
图2为本申请实施例线控底盘结构图。
图3为本申请实施例方法具体实施流程图。
图4为实施例H∞反馈控制结构图。
具体实施方式
为了便于本领域技术人员的理解，下面结合实施例与附图对本发明作进一步的说明，实施方式提及的内容并非对本发明的限定。
参照图1所示，本发明的一种智能交通环境下的线控底盘信息物理***，包括：SoS级CPS、***级CPS和单元级CPS；通过网络，多个单元级CPS与一个***级CPS之间实现数据传输，多个***级CPS与一个SoS级CPS之间实现数据传输；
单元级CPS为线控底盘，参照图2所示，包括：驾驶员输入模块、基本控制模块、执行模块和环境感知模块；
所述驾驶员输入模块包括：油门踏板及其行程和力传感器、制动踏板及其行程和力传感器、方向盘及其转角和转矩传感器、车轮转角传感器，用于感知驾驶员对车辆输入 的驱动、制动、转向信息，实现驾驶员操作意图的提取；
所述基本控制模块对各传感器采集的数据进行处理，根据当前工况制定最优行驶策略，并传递给执行模块；
所述执行模块用于接收上述基本控制模块的最优行驶策略，并对车辆进行操控；
其中，所述执行模块包括：车轮、轮毂电机、转向执行电机、转向控制器、转向轴、传动轴、齿轮齿条转向器、转向拉杆、制动控制器、制动执行机构、制动电机、驱动控制器、驱动执行机构。
其中，所述最优行驶策略为符合当前工况的执行模块的执行状态，最优行驶策略包括：最优转向策略、最优制动策略、最优驱动策略、最优复合行驶策略；所述最优转向策略、最优制动策略、最优驱动策略分别在转向、制动、驱动单一工况下制定；所述最优复合行驶策略为最优转向策略与最优制动策略或最优驱动策略的组合；所述最优转向策略包括转向执行电机实际能耗最小、车轮转角无需驾驶员修正；所述最优制动策略包括制动电机能耗最小、制动执行机构执行时间最短、制动执行机构执行过程中无需驾驶员修正；所述最优驱动策略包括轮毂电机能耗最小且驱动执行机构执行时间最短、驱动执行机构执行过程中无需驾驶员修正。
所述环境感知模块，包括：探测设备、定位设备和通信设备；所述探测设备用于感知车辆外部的信息和前方路况信息；定位设备用于对车辆位置进行定位；通信设备用于车辆与车辆之间通讯、车辆与基站之间通讯，以获取车辆行驶过程中实时工况信息；
其中，所述基本控制模块包括：中央控制单元、转向控制单元、制动控制单元、驱动控制单元；所述中央控制单元用于监测和控制转向控制单元、制动控制单元和驱动控制单元，接收各传感器信号，用于计算车速，分配转向、制动和驱动力。
***级CPS为监管平台，包括：协同控制模块、实时监控和诊断模块；用于监管同一道路上装载线控底盘的车辆的驾驶行为；
所述协同控制模块用于获取监管的线控底盘的传感器数据和执行模块发出的执行信息，通过信息交互和实时分析获得当前工况下的局部最优方案，对基本控制模块发出控制信号；所述实时监控和诊断模块用于监控和诊断装载线控底盘的车辆的驾驶情况；
SoS级CPS为大数据平台，包括：数据存储单元、数据交互模块、数据分析模块，并通过互联网与各监管平台进行数据传输；
所述数据存储单元用于存储传输至大数据平台的数据；所述数据交互模块用于实现线控底盘、监管平台之间传感器数据、执行信息的传输；所述数据分析模块用于分析传 输至大数据平台的数据，得出线控底盘理想操作，并判断线控底盘的驾驶操作是否为理想操作；
此外，所述车辆外部的信息包括：道路车道线、路面箭头标志、路旁交通标志牌、交通红绿灯的信息。
所述前方路况信息包括前方的凹凸障碍物、车辆、行人。
所述局部最优方案为同一监管平台的所有线控底盘的行驶行为，包括转向、制动、驱动、转向且制动、转向且驱动。
所述传输至大数据平台的数据包括：传感器数据、执行信息、车辆外部信息、前方路况信息、位置信息、车辆与车辆通讯信息、车辆与基站通讯信息、监管平台生成的局部最优方案。
所述线控底盘理想操作为理想操作数据库中数据，包括理想方向盘转角、理想制动踏板开度、理想加速踏板开度；所述理想方向盘转角为数据分析模块规划的期望路径所需的方向盘转角大小；所述理想制动踏板开度为数据分析模块规划的与前方和周围障碍物保持交通安全距离且保证驾驶员驾驶舒适度的制动踏板开度；所述理想加速踏板开度为数据分析模块规划的保证驾驶员驾驶舒适度且与周围障碍物保持交通安全距离的符合交通环境速度要求的加速踏板开度。
所述理想操作数据库为离线同步数据库，由车辆工程师经验数据、汽车动力学和运动学模型数据、交通环境中汽车行驶数据离线同步组成；理想操作数据库中数据均处于安全驾驶且保证驾驶员舒适度范围；所述车辆工程师经验数据包括驾驶员转向、制动、驱动、转向与制动或驱动情况下驾驶舒适度数据，驾驶员转向、制动、驱动的操作力与车速、加速度的非线性数学模型数据；所述汽车动力学和运动学模型包括由牛顿运动定律计算的转向、制动、驱动执行时的动力学和运动学方程，由基尔霍夫定律计算的转向、制动、驱动执行时的转向执行电机、制动电机、驱动电机、轮毂电机的电流方程；所述交通环境中汽车行驶数据为联网线控底盘汽车在联网情况下储存的驾驶信息数据。进一步地，所述驾驶员输入模块、基本控制模块、执行模块之间的转向连接关系为：方向盘转角和转矩传感器集成于与方向盘，方向盘通过转向轴与传动轴连接，传动轴连接齿轮齿条转向器，齿轮齿条转向器与转向拉杆连接；转向执行电机固定在传动轴上，当方向盘转动时转角和转矩传感器工作，转向控制器将采集方向盘转角和转矩、车轮转角信息传送至转向控制单元，转向控制单元根据传感器信息控制转向执行电机的电流输出，进而控制传动轴的转向；转向控制器与轮毂电机连接，控制四个车轮的转动。
所述驾驶员输入模块、基本控制模块、执行模块之间的制动连接关系为：踩下制动踏板时，制动踏板的行程和力传感器工作，制动控制器将采集制动踏板的行程和力传感器信息传送至制动控制单元，制动控制单元根据传感器信息控制制动电机的电流输出，进而控制制动执行机构的执行状态，实现对车辆的制动；制动控制器与轮毂电机连接，控制车轮制动时的转动状态。
所述驾驶员输入模块、基本控制模块、执行模块之间的驱动连接关系为：踩下油门踏板时，油门踏板的行程和力传感器工作，驱动控制器将采集油门踏板的行程和力传感器信息传送至驱动控制单元，驱动控制单元根据传感器信息控制驱动执行机构的执行状态，实现对车辆的驱动；驱动控制器与车轮的轮毂电机连接，控制车轮加速时的转动状态。
所述轮毂电机包括：左前轮轮毂电机、右前轮轮毂电机、左后轮轮毂电机、右后轮轮毂电机；四个轮毂电机分别集成在相应的四个车轮轮毂中，用于驱动车轮。
线控底盘、监管平台、大数据平台通过互联网完成数据传输；
所述数据传输过程为：线控底盘在驾驶员完成驾驶操作后获取驾驶员操作信息和环境信息，并传输至监管平台；监管平台的实时监控和诊断模块对线控底盘传输的驾驶员操作信息和环境信息进行实时监控和诊断，将诊断结果传输至大数据平台；大数据平台完成信息存储和交互，通过数据分析模块获得线控底盘的操作行为信息，传输至监管平台；监管平台的协同控制模块根据大数据平台传输的信息生成局部最优方案，传输至线控底盘；线控底盘的基本控制模块根据局部最优方案形成最优行驶策略，执行模块根据最优行驶策略对车辆进行控制。
如图3所示，本实施例还提供了基于上述***的智能交通环境下的线控底盘信息物理***的控制方法，具体步骤如下：
1)驾驶员发出操作信号；所述驾驶员发出的操作信号包括：转向、制动、驱动、复合操作信号，其中复合操作信号为转向与制动或驱动的组合。
2)获取线控底盘的环境感知模块的信息和驾驶员输入模块的传感器信息；
所述步骤2)中通过传感器获取车辆当前方向盘转角和转矩、车轮转角、制动踏板行程、油门踏板行程，通过环境感知模块中的探测设备、定位设备和通讯设备获取当前工况下车辆外部的信息、前方路况信息、位置信息、车辆与车辆之间通讯信息、车辆与基站之间通讯信息。
3)基本控制模块根据驾驶员输入模块的传感器信息判断驾驶员的操作，将驾驶员 操作信息和环境感知模块的信息传输至监管平台；驾驶员操作包括转向、制动、驱动、复合操作，其中复合操作包括转向与制动或驱动的组合。
4)监管平台通过网络对线控底盘的信息进行实时监控和诊断，判断当前驾驶员的操作是否符合当前工况；若符合工况将监管平台获取的驾驶员操作和环境感知模块的信息传送至大数据平台；若不符合工况，监管平台根据环境感知模块的信息调整驾驶员操作以符合当前工况，将环境感知模块的信息和调整后的驾驶员操作信息传送至大数据平台；
所述步骤4)中若任一道路的监管平台出现故障，则由其他任一道路的监管平台接管出现故障的监管平台的数据信息，对当前道路内及出现故障的监管平台对应道路的线控底盘进行实时监控和诊断，保证交通环境信息的稳定；
所述步骤4)的当前工况包括转向工况、制动工况、加速工况、转向工况与制动工况或加速工况的组合工况；其中转向工况包括通过弯道、超车、变道；制动工况包括前方车辆减速且与前方车辆距离小于交通安全距离、紧急避障停车、车速高于限速时通过限速路段；其中加速工况包括车辆起步、车速低于限速路段时通过限速路段、超车；
5)大数据平台对监管平台传送的操作信息进行存储；
6)大数据平台对监管平台传送的驾驶员操作信息进行分析；若监管平台中的驾驶员操作信息分析结果为理想驾驶操作，则将驾驶员操作信息反馈至监管平台；若驾驶员操作信息分析结果与理想驾驶操作信息存在误差，则将数据分析得到的理想驾驶操作信息反馈至监管平台；
所述步骤6)中当前驾驶员的操作与理想驾驶操作存在误差，则由中央控制单元控制转向、制动、驱动控制单元以驱动轮毂电机、转向执行电机、制动电机输出附加控制量，以最小化驾驶员的操作与理想驾驶操作的误差；其中所利用的控制算法为H∞反馈控制算法，参照图4所示，具体包括以下内容：
61)驾驶员输出的方向盘转角θ sw和理想方向盘转角
Figure PCTCN2021138518-appb-000002
的偏差表示为e 1；驾驶员输出的制动踏板开度p和理想制动踏板开度p *的偏差表示为e 2；驾驶员输出的加速踏板开度q和理想加速踏板开度q *的偏差表示为e 3；
62)偏差e 1，e 2，e 3为H∞反馈控制器K(s)的输入，反馈控制器K(s)根据输入偏差e 1，e 2，e 3计算出转向执行电机、制动电机和轮毂电机需要输出的附加转角θ 1，θ 2，θ 3，则中央控制单元和转向控制单元、制动控制单元、驱动控制单元分别控制转向执行 电机、制动电机、轮毂电机输出相应的附加转角θ 1，θ 2，θ 3；
63)附加转角θ 1，θ 2，θ 3作用到线控底盘***，进而影响车辆的行驶状态，同时驾驶员根据当前车辆状态进行相应地驾驶操作，则得到一组新的偏差e 4，e 5，e 6；
64)重复步骤61)—63)，直至偏差e i(i＝1,2,3,...)消除。
7)监管平台根据反馈信息形成车辆实时的局部最优方案，将局部最优方案通过互联网反馈给当前监管平台所监管的线控底盘；
8)中央控制单元将生成对应局部最优方案的最优行驶策略，并传递给转向控制单元、制动控制单元、驱动控制单元，来控制执行模块中电机的输出电流，从而使控制器对执行模块中其他执行机构进行控制，完成对车辆的输出；
所述步骤8)中电机包括转向执行电机，制动电机，轮毂电机；控制器包括转向控制器，制动控制器，驱动控制器；其他执行机构为执行模块中除执行电机，制动电机，轮毂电机，转向控制器，制动控制器，驱动控制器的执行机构。
本发明具体应用途径很多，以上所述仅是本发明的优选实施方式，应当指出，对于本技术领域的普通技术人员来说，在不脱离本发明原理的前提下，还可以作出若干改进，这些改进也应视为本发明的保护范围。

Claims (10)

  1. 一种智能交通环境下的线控底盘信息物理***，其特征在于，包括：SoS级CPS、***级CPS和单元级CPS；多个单元级CPS与一个***级CPS之间实现数据传输，多个***级CPS与一个SoS级CPS之间实现数据传输；
    单元级CPS为线控底盘，包括：驾驶员输入模块、基本控制模块、执行模块和环境感知模块；
    所述驾驶员输入模块包括：油门踏板及其行程和力传感器、制动踏板及其行程和力传感器、方向盘及其转角和转矩传感器、车轮转角传感器，用于感知驾驶员对车辆输入的驱动、制动、转向信息，实现驾驶员操作意图的提取；
    所述基本控制模块对各传感器采集的数据进行处理，根据当前工况制定最优行驶策略，并传递给执行模块；
    所述执行模块用于接收上述基本控制模块的最优行驶策略，并对车辆进行操控；
    所述环境感知模块，包括：探测设备、定位设备和通信设备；所述探测设备用于感知车辆外部的信息和前方路况信息；定位设备用于对车辆位置进行定位；通信设备用于车辆与车辆之间通讯、车辆与基站之间通讯，以获取车辆行驶过程中实时工况信息；
    ***级CPS为监管平台，包括：协同控制模块、实时监控和诊断模块；用于监管同一道路上装载线控底盘的车辆的驾驶行为；
    所述协同控制模块用于获取监管的线控底盘的传感器数据和执行模块发出的执行信息，通过信息交互和实时分析获得当前工况下的局部最优方案，对基本控制模块发出控制信号；所述实时监控和诊断模块用于监控和诊断装载线控底盘的车辆的驾驶情况；
    SoS级CPS为大数据平台，包括：数据存储单元、数据交互模块、数据分析模块，并通过互联网与各监管平台进行数据传输；
    所述数据存储单元用于存储传输至大数据平台的数据；所述数据交互模块用于实现线控底盘、监管平台之间传感器数据、执行信息的传输；所述数据分析模块用于分析传输至大数据平台的数据，得出线控底盘理想操作，并判断线控底盘的驾驶操作是否为理想操作。
  2. 根据权利要求1所述的智能交通环境下的线控底盘信息物理***，其特征在于，所述基本控制模块包括：中央控制单元、转向控制单元、制动控制单元、驱动控制单元；所述中央控制单元用于监测和控制转向控制单元、制动控制单元和驱动控制单元，接收各传感器信号，用于计算车速，分配转向、制动和驱动力。
  3. 根据权利要求1所述的智能交通环境下的线控底盘信息物理***，其特征在于，所述最优行驶策略为符合当前工况的执行模块的执行状态，最优行驶策略包括：最优转向策略、最优制动策略、最优驱动策略、最优复合行驶策略；所述最优转向策略、最优制动策略、最优驱动策略分别在转向、制动、驱动单一工况下制定；所述最优复合行驶策略为最优转向策略与最优制动策略或最优驱动策略的组合；所述最优转向策略包括转向执行电机实际能耗最 小、车轮转角无需驾驶员修正；所述最优制动策略包括制动电机能耗最小、制动执行机构执行时间最短、制动执行机构执行过程中无需驾驶员修正；所述最优驱动策略包括轮毂电机能耗最小且驱动执行机构执行时间最短、驱动执行机构执行过程中无需驾驶员修正。
  4. 根据权利要求1所述的智能交通环境下的线控底盘信息物理***，其特征在于，所述线控底盘理想操作为理想操作数据库中数据，包括理想方向盘转角、理想制动踏板开度、理想加速踏板开度；所述理想方向盘转角为数据分析模块规划的期望路径所需的方向盘转角大小；所述理想制动踏板开度为数据分析模块规划的与前方和周围障碍物保持交通安全距离且保证驾驶员驾驶舒适度的制动踏板开度；所述理想加速踏板开度为数据分析模块规划的保证驾驶员驾驶舒适度且与周围障碍物保持交通安全距离的符合交通环境速度要求的加速踏板开度。
  5. 根据权利要求1所述的智能交通环境下的线控底盘信息物理***，其特征在于，所述理想操作数据库为离线同步数据库，由车辆工程师经验数据、汽车动力学和运动学模型数据、交通环境中汽车行驶数据离线同步组成；理想操作数据库中数据均处于安全驾驶且保证驾驶员舒适度范围；所述车辆工程师经验数据包括驾驶员转向、制动、驱动、转向与制动或驱动情况下驾驶舒适度数据，驾驶员转向、制动、驱动的操作力与车速、加速度的非线性数学模型数据；所述汽车动力学和运动学模型包括由牛顿运动定律计算的转向、制动、驱动执行时的动力学和运动学方程，由基尔霍夫定律计算的转向、制动、驱动执行时的转向执行电机、制动电机、驱动电机、轮毂电机的电流方程；所述交通环境中汽车行驶数据为联网线控底盘汽车在联网情况下储存的驾驶信息数据。
  6. 根据权利要求1所述的智能交通环境下的线控底盘信息物理***，其特征在于，所述驾驶员输入模块、基本控制模块、执行模块之间的制动连接关系为：踩下制动踏板时，制动踏板的行程和力传感器工作，制动控制器将采集制动踏板的行程和力传感器信息传送至制动控制单元，制动控制单元根据传感器信息控制制动电机的电流输出，进而控制制动执行机构的执行状态，实现对车辆的制动；制动控制器与轮毂电机连接，控制车轮制动时的转动状态。
  7. 一种智能交通环境下的线控底盘信息物理***的控制方法，基于权利要求1-6中任意一项所述***，其特征在于，步骤如下：
    1)驾驶员发出操作信号；
    2)获取线控底盘的环境感知模块的信息和驾驶员输入模块的传感器信息；
    3)基本控制模块根据驾驶员输入模块的传感器信息判断驾驶员的操作，将驾驶员操作信息和环境感知模块的信息传输至监管平台；
    4)监管平台对线控底盘的信息进行实时监控和诊断，判断当前驾驶员的操作是否符合当前工况；若符合工况将监管平台获取的驾驶员操作和环境感知模块的信息传送至大数据平台；若不符合工况，监管平台根据环境感知模块的信息调整驾驶员操作以符合当前工况，将环境 感知模块的信息和调整后的驾驶员操作信息传送至大数据平台；
    5)大数据平台对监管平台传送的操作信息进行存储；
    6)大数据平台对监管平台传送的驾驶员操作信息进行分析；若监管平台中的驾驶员操作信息分析结果为理想驾驶操作，则将驾驶员操作信息反馈至监管平台；若驾驶员操作信息分析结果与理想驾驶操作信息存在误差，则将数据分析得到的理想驾驶操作信息反馈至监管平台；
    7)监管平台根据反馈信息形成车辆实时的局部最优方案，将局部最优方案反馈给当前监管平台所监管的线控底盘；
    8)中央控制单元将生成对应局部最优方案的最优行驶策略，并传递给转向控制单元、制动控制单元、驱动控制单元，来控制执行模块中电机的输出电流，从而使控制器对执行模块中其他执行机构进行控制，完成对车辆的输出。
  8. 根据权利要求7所述的智能交通环境下的线控底盘信息物理***的控制方法，其特征在于，所述步骤2)中通过传感器获取车辆当前方向盘转角和转矩、车轮转角、制动踏板行程、油门踏板行程，通过环境感知模块中的探测设备、定位设备和通讯设备获取当前工况下车辆外部的信息、前方路况信息、位置信息、车辆与车辆之间通讯信息、车辆与基站之间通讯信息。
  9. 根据权利要求7所述的智能交通环境下的线控底盘信息物理***的控制方法，其特征在于，所述步骤4)中若任一道路的监管平台出现故障，则由其他任一道路的监管平台接管出现故障的监管平台的数据信息，对当前道路内及出现故障的监管平台对应道路的线控底盘进行实时监控和诊断，保证交通环境信息的稳定。
  10. 根据权利要求7所述的智能交通环境下的线控底盘信息物理***的控制方法，其特征在于，所述步骤6)中当前驾驶员的操作与理想驾驶操作存在误差，则由中央控制单元控制转向、制动、驱动控制单元以驱动轮毂电机、转向执行电机、制动电机输出附加控制量，以最小化驾驶员的操作与理想驾驶操作的误差；所利用的控制算法为H∞反馈控制算法，具体包括：
    61)驾驶员输出的方向盘转角θ sw和理想方向盘转角
    Figure PCTCN2021138518-appb-100001
    的偏差表示为e 1；驾驶员输出的制动踏板开度p和理想制动踏板开度p *的偏差表示为e 2；驾驶员输出的加速踏板开度q和理想加速踏板开度q *的偏差表示为e 3；
    62)偏差e 1，e 2，e 3为H∞反馈控制器K(s)的输入，反馈控制器K(s)根据输入偏差e 1，e 2，e 3计算出转向执行电机、制动电机和轮毂电机需要输出的附加转角θ 1，θ 2，θ 3，则中央控制单元和转向控制单元、制动控制单元、驱动控制单元分别控制转向执行电机、制动电机、 轮毂电机输出相应的附加转角θ 1，θ 2，θ 3；
    63)附加转角θ 1，θ 2，θ 3作用到线控底盘***，进而影响车辆的行驶状态，同时驾驶员根据当前车辆状态进行相应地驾驶操作，则得到一组新的偏差e 4，e 5，e 6；
    64)重复步骤61)—63)，直至偏差e i消除，i＝1,2,3,...。
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Families Citing this family (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112874502B (zh) * 2021-03-01 2022-07-12 南京航空航天大学 一种智能交通环境下的线控底盘信息物理***及控制方法
CN113335293B (zh) * 2021-06-22 2022-09-02 吉林大学 一种线控底盘的高速公路路面探测***
CN113581278B (zh) * 2021-07-20 2023-03-28 浙江万安科技股份有限公司 一种多模式线控底盘***及其控制方法
CN113895448B (zh) * 2021-10-20 2023-03-10 清华大学 域控制器间的协同交互控制架构及其控制方法
CN114228496A (zh) * 2021-12-31 2022-03-25 优跑汽车技术(上海)有限公司 驱动控制方法、装置、车辆底盘和电动车辆
CN114647235B (zh) * 2022-05-24 2022-10-04 北京理工大学深圳汽车研究院(电动车辆国家工程实验室深圳研究院) 一种线控底盘的控制方法、联合控制***及服务器

Citations (13)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20110112716A1 (en) * 2009-11-09 2011-05-12 Hyundai Motor Company Apparatus for controlling vehicle chassis having integrated fail safe controller
CN107031600A (zh) * 2016-10-19 2017-08-11 东风汽车公司 基于高速公路的自动驾驶***
CN108036953A (zh) * 2017-12-14 2018-05-15 燕山大学 轮毂电机驱动汽车集成设计与协同控制试验平台及实现方法
CN108437978A (zh) * 2018-05-14 2018-08-24 武汉理工大学 四轮毂电驱车辆行驶路面自动识别与稳定性集成控制方法
CN108725453A (zh) * 2018-06-11 2018-11-02 南京航空航天大学 基于驾驶员模型和操纵逆动力学的人机共驾控制***及其切换模式
CN108995655A (zh) * 2018-07-06 2018-12-14 北京理工大学 一种驾驶员驾驶意图识别方法及***
CN109435961A (zh) * 2018-11-13 2019-03-08 常熟理工学院 一种基于驾驶人特性的全线控电动汽车底盘协调控制方法
CN110466359A (zh) * 2019-08-05 2019-11-19 东风汽车集团有限公司 轮毂四驱纯电动汽车扭矩矢量控制***及控制方法
CN111332302A (zh) * 2020-03-24 2020-06-26 常州工学院 一种四轮独立驱动电动汽车控制方法及***
CN111775721A (zh) * 2020-07-14 2020-10-16 清华大学 全矢量控制底盘结构、全矢量控制汽车的控制方法和装置
CN111994086A (zh) * 2020-07-14 2020-11-27 南京天航智能装备研究院有限公司 一种智能线控底盘***及解耦控制方法
CN112084698A (zh) * 2020-07-13 2020-12-15 南京航空航天大学 一种汽车智能线控底盘***及其不确定优化方法
CN112874502A (zh) * 2021-03-01 2021-06-01 南京航空航天大学 一种智能交通环境下的线控底盘信息物理***及控制方法

Family Cites Families (28)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2007253726A (ja) * 2006-03-22 2007-10-04 Honda Motor Co Ltd 車両制御装置および車両制御方法
DE102007057822B4 (de) * 2007-11-30 2016-10-27 Dr. Ing. H.C. F. Porsche Aktiengesellschaft Regelungsverfahren für ein Fahrwerk eines Kraftfahrzeugs
CN203324777U (zh) * 2013-06-01 2013-12-04 青岛科技大学 基于cps的家庭智能双平台协同控制***
DE102015225617A1 (de) * 2015-02-06 2016-08-11 Robert Bosch Gmbh Verfahren zur Überwachung eines Drive-by-Wire-Systems eines Kraftfahrzeugs
EP3305620B1 (en) * 2015-06-03 2019-08-07 Nissan Motor Co., Ltd. Vehicle control device and vehicle control method
JP6798779B2 (ja) * 2015-11-04 2020-12-09 トヨタ自動車株式会社 地図更新判定システム
US10919520B1 (en) * 2016-08-03 2021-02-16 Apple Inc. Integrated chassis control
US10377375B2 (en) * 2016-09-29 2019-08-13 The Charles Stark Draper Laboratory, Inc. Autonomous vehicle: modular architecture
US10599150B2 (en) * 2016-09-29 2020-03-24 The Charles Stark Kraper Laboratory, Inc. Autonomous vehicle: object-level fusion
US10101745B1 (en) * 2017-04-26 2018-10-16 The Charles Stark Draper Laboratory, Inc. Enhancing autonomous vehicle perception with off-vehicle collected data
JP6683178B2 (ja) * 2017-06-02 2020-04-15 トヨタ自動車株式会社 自動運転システム
US10899340B1 (en) * 2017-06-21 2021-01-26 Apple Inc. Vehicle with automated subsystems
KR101989102B1 (ko) * 2017-09-13 2019-06-13 엘지전자 주식회사 차량용 운전 보조 장치 및 그 제어 방법
US10661785B2 (en) * 2017-12-15 2020-05-26 Tenneco Automotive Operating Company Inc. Systems and methods for integrated chassis control in ground vehicles
US10902165B2 (en) * 2018-01-09 2021-01-26 The Charles Stark Draper Laboratory, Inc. Deployable development platform for autonomous vehicle (DDPAV)
CN108327702A (zh) * 2018-01-26 2018-07-27 东风汽车集团有限公司 一种四轮轮毂电机独立驱动控制方法
CA3159409A1 (en) * 2018-07-07 2020-01-16 Peloton Technology, Inc. Control of automated following in vehicle convoys
CN108891409A (zh) * 2018-08-29 2018-11-27 固安海高汽车技术有限公司 一种智能驾驶***和中央域控制器及其方法
CN109515512B (zh) * 2018-10-18 2020-06-16 合肥工业大学 用于轮式独立驱动车辆的线控差动转向***的控制方法
CN109878519A (zh) * 2019-04-01 2019-06-14 南京航空航天大学 一种分布式电驱动汽车拥堵跟随控制***和方法
WO2021045255A1 (ko) * 2019-09-04 2021-03-11 엘지전자 주식회사 경로 제공 장치 및 그것의 경로 제공 방법
US11518402B2 (en) * 2020-02-28 2022-12-06 Nissan North America, Inc. System and method for controlling a vehicle using contextual navigation assistance
US11614335B2 (en) * 2020-12-22 2023-03-28 Nissan North America, Inc. Route planner optimization for hybrid-electric vehicles
US11993281B2 (en) * 2021-02-26 2024-05-28 Nissan North America, Inc. Learning in lane-level route planner
US20220306156A1 (en) * 2021-03-29 2022-09-29 Nissan North America, Inc. Route Planner and Decision-Making for Exploration of New Roads to Improve Map
US11945441B2 (en) * 2021-03-31 2024-04-02 Nissan North America, Inc. Explainability and interface design for lane-level route planner
US11702075B2 (en) * 2021-04-30 2023-07-18 Nissan North America, Inc. System and method for proactive lane assist
CN116022143A (zh) * 2021-10-27 2023-04-28 通用汽车环球科技运作有限责任公司 基于连续交通灯的时序的车辆速度规划

Patent Citations (13)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20110112716A1 (en) * 2009-11-09 2011-05-12 Hyundai Motor Company Apparatus for controlling vehicle chassis having integrated fail safe controller
CN107031600A (zh) * 2016-10-19 2017-08-11 东风汽车公司 基于高速公路的自动驾驶***
CN108036953A (zh) * 2017-12-14 2018-05-15 燕山大学 轮毂电机驱动汽车集成设计与协同控制试验平台及实现方法
CN108437978A (zh) * 2018-05-14 2018-08-24 武汉理工大学 四轮毂电驱车辆行驶路面自动识别与稳定性集成控制方法
CN108725453A (zh) * 2018-06-11 2018-11-02 南京航空航天大学 基于驾驶员模型和操纵逆动力学的人机共驾控制***及其切换模式
CN108995655A (zh) * 2018-07-06 2018-12-14 北京理工大学 一种驾驶员驾驶意图识别方法及***
CN109435961A (zh) * 2018-11-13 2019-03-08 常熟理工学院 一种基于驾驶人特性的全线控电动汽车底盘协调控制方法
CN110466359A (zh) * 2019-08-05 2019-11-19 东风汽车集团有限公司 轮毂四驱纯电动汽车扭矩矢量控制***及控制方法
CN111332302A (zh) * 2020-03-24 2020-06-26 常州工学院 一种四轮独立驱动电动汽车控制方法及***
CN112084698A (zh) * 2020-07-13 2020-12-15 南京航空航天大学 一种汽车智能线控底盘***及其不确定优化方法
CN111775721A (zh) * 2020-07-14 2020-10-16 清华大学 全矢量控制底盘结构、全矢量控制汽车的控制方法和装置
CN111994086A (zh) * 2020-07-14 2020-11-27 南京天航智能装备研究院有限公司 一种智能线控底盘***及解耦控制方法
CN112874502A (zh) * 2021-03-01 2021-06-01 南京航空航天大学 一种智能交通环境下的线控底盘信息物理***及控制方法

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