WO2023174327A1 - 一种协同控制模块、自适应巡航系统及其控制方法、交通工具 - Google Patents

一种协同控制模块、自适应巡航系统及其控制方法、交通工具 Download PDF

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Publication number
WO2023174327A1
WO2023174327A1 PCT/CN2023/081599 CN2023081599W WO2023174327A1 WO 2023174327 A1 WO2023174327 A1 WO 2023174327A1 CN 2023081599 W CN2023081599 W CN 2023081599W WO 2023174327 A1 WO2023174327 A1 WO 2023174327A1
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Prior art keywords
vehicle
control
suspension
adaptive cruise
speed
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PCT/CN2023/081599
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English (en)
French (fr)
Inventor
汪若尘
刘伟
丁仁凯
蒋俞
孟祥鹏
孙泽宇
孙东
Original Assignee
江苏大学
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Application filed by 江苏大学 filed Critical 江苏大学
Priority to GB2319355.0A priority Critical patent/GB2621966A/en
Publication of WO2023174327A1 publication Critical patent/WO2023174327A1/zh

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    • BPERFORMING OPERATIONS; TRANSPORTING
    • B60VEHICLES IN GENERAL
    • B60WCONJOINT 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
    • B60W30/00Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units
    • B60W30/14Adaptive cruise control
    • B60W30/143Speed control
    • BPERFORMING OPERATIONS; TRANSPORTING
    • B60VEHICLES IN GENERAL
    • B60GVEHICLE SUSPENSION ARRANGEMENTS
    • B60G17/00Resilient suspensions having means for adjusting the spring or vibration-damper characteristics, for regulating the distance between a supporting surface and a sprung part of vehicle or for locking suspension during use to meet varying vehicular or surface conditions, e.g. due to speed or load
    • B60G17/015Resilient suspensions having means for adjusting the spring or vibration-damper characteristics, for regulating the distance between a supporting surface and a sprung part of vehicle or for locking suspension during use to meet varying vehicular or surface conditions, e.g. due to speed or load the regulating means comprising electric or electronic elements
    • B60G17/0195Resilient suspensions having means for adjusting the spring or vibration-damper characteristics, for regulating the distance between a supporting surface and a sprung part of vehicle or for locking suspension during use to meet varying vehicular or surface conditions, e.g. due to speed or load the regulating means comprising electric or electronic elements characterised by the regulation being combined with other vehicle control systems
    • BPERFORMING OPERATIONS; TRANSPORTING
    • B60VEHICLES IN GENERAL
    • B60WCONJOINT 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
    • B60W10/00Conjoint control of vehicle sub-units of different type or different function
    • B60W10/22Conjoint control of vehicle sub-units of different type or different function including control of suspension systems
    • BPERFORMING OPERATIONS; TRANSPORTING
    • B60VEHICLES IN GENERAL
    • B60GVEHICLE SUSPENSION ARRANGEMENTS
    • B60G2400/00Indexing codes relating to detected, measured or calculated conditions or factors
    • B60G2400/10Acceleration; Deceleration
    • B60G2400/102Acceleration; Deceleration vertical
    • BPERFORMING OPERATIONS; TRANSPORTING
    • B60VEHICLES IN GENERAL
    • B60GVEHICLE SUSPENSION ARRANGEMENTS
    • B60G2400/00Indexing codes relating to detected, measured or calculated conditions or factors
    • B60G2400/20Speed
    • B60G2400/204Vehicle speed
    • BPERFORMING OPERATIONS; TRANSPORTING
    • B60VEHICLES IN GENERAL
    • B60GVEHICLE SUSPENSION ARRANGEMENTS
    • B60G2400/00Indexing codes relating to detected, measured or calculated conditions or factors
    • B60G2400/30Propulsion unit conditions
    • B60G2400/38Speed of engine rotation
    • BPERFORMING OPERATIONS; TRANSPORTING
    • B60VEHICLES IN GENERAL
    • B60GVEHICLE SUSPENSION ARRANGEMENTS
    • B60G2400/00Indexing codes relating to detected, measured or calculated conditions or factors
    • B60G2400/30Propulsion unit conditions
    • B60G2400/39Brake pedal position
    • BPERFORMING OPERATIONS; TRANSPORTING
    • B60VEHICLES IN GENERAL
    • B60GVEHICLE SUSPENSION ARRANGEMENTS
    • B60G2400/00Indexing codes relating to detected, measured or calculated conditions or factors
    • B60G2400/80Exterior conditions
    • B60G2400/82Ground surface
    • B60G2400/821Uneven, rough road sensing affecting vehicle body vibration
    • BPERFORMING OPERATIONS; TRANSPORTING
    • B60VEHICLES IN GENERAL
    • B60GVEHICLE SUSPENSION ARRANGEMENTS
    • B60G2400/00Indexing codes relating to detected, measured or calculated conditions or factors
    • B60G2400/90Other conditions or factors
    • BPERFORMING OPERATIONS; TRANSPORTING
    • B60VEHICLES IN GENERAL
    • B60GVEHICLE SUSPENSION ARRANGEMENTS
    • B60G2401/00Indexing codes relating to the type of sensors based on the principle of their operation
    • B60G2401/14Photo or light sensitive means, e.g. Infrared
    • B60G2401/142Visual Display Camera, e.g. LCD
    • BPERFORMING OPERATIONS; TRANSPORTING
    • B60VEHICLES IN GENERAL
    • B60GVEHICLE SUSPENSION ARRANGEMENTS
    • B60G2600/00Indexing codes relating to particular elements, systems or processes used on suspension systems or suspension control systems
    • B60G2600/20Manual control or setting means
    • BPERFORMING OPERATIONS; TRANSPORTING
    • B60VEHICLES IN GENERAL
    • B60GVEHICLE SUSPENSION ARRANGEMENTS
    • B60G2800/00Indexing codes relating to the type of movement or to the condition of the vehicle and to the end result to be achieved by the control action
    • B60G2800/90System Controller type
    • B60G2800/91Suspension Control
    • BPERFORMING OPERATIONS; TRANSPORTING
    • B60VEHICLES IN GENERAL
    • B60GVEHICLE SUSPENSION ARRANGEMENTS
    • B60G2800/00Indexing codes relating to the type of movement or to the condition of the vehicle and to the end result to be achieved by the control action
    • B60G2800/90System Controller type
    • B60G2800/982Active Cruise Control, e.g. DISTRONIC type
    • YGENERAL 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
    • Y02TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02TCLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
    • Y02T10/00Road transport of goods or passengers
    • Y02T10/80Technologies aiming to reduce greenhouse gasses emissions common to all road transportation technologies
    • Y02T10/84Data processing systems or methods, management, administration

Definitions

  • the invention belongs to the technical fields of assisted driving and vehicle chassis dynamics control, and specifically relates to an adaptive cruise system and a control method thereof.
  • Adaptive cruise is an important intelligent assistance system during current vehicle driving. It can greatly reduce the fatigue of long-distance driving and provide drivers with a more relaxed and comfortable driving experience.
  • Cruise control actually refers to vehicle speed control, which belongs to vehicle longitudinal dynamics control.
  • Current research on adaptive cruise control mainly focuses on vehicle speed tracking and obstacle avoidance, and few studies consider the vehicle's ride comfort and handling stability during cruising. Vehicle ride comfort and handling stability involve vertical dynamics control. Although the controllable suspension system can improve the vertical dynamics performance of the vehicle during driving through semi-active/active control, the control effect is greatly affected by the driving speed. big. On the same driving road surface, higher driving speed will lead to poorer ride comfort and handling stability.
  • Current research has failed to provide an effective solution on how to coordinate adaptive cruise and controllable suspension control and improve vehicle vertical dynamic performance during cruise through longitudinal and vertical cooperative control.
  • the present invention provides an adaptive cruise system and a control method thereof, which can effectively improve the vertical dynamic performance of the vehicle during cruising.
  • the present invention achieves the above technical objectives through the following technical means.
  • An adaptive cruise and controllable suspension cooperative control module including an adaptive cruise control sub-module and a suspension control sub-module;
  • the adaptive cruise control submodule is used to process adaptive cruise control instructions.
  • the adaptive cruise control instructions include intelligent cruise speed setting instructions, and calculate the optimal cruise speed during the intelligent cruise speed setting process;
  • the suspension control submodule switches corresponding controllable suspension control parameters according to the vehicle's real-time dynamic performance requirements.
  • the adaptive cruise control sub-module determines the root mean square value of the weighted acceleration of the expected vehicle body center of mass based on the set target comfort level, and calculates the optimal cruising speed based on the current driving road surface information.
  • controllable suspension control parameters are determined by:
  • the comprehensive performance evaluation function takes into account both vehicle ride comfort and handling stability. ;
  • An adaptive cruise system includes the above collaborative control module.
  • the adaptive cruise and controllable suspension collaborative control module receives signals from the sensor module, the driving environment intelligent perception module and the vehicle state response information estimation module, and sends the optimal cruise speed to the power control module. .
  • the vehicle sensor module is used to obtain vehicle speed and brake pedal signals, road surface measurement signals, vehicle distance signals, and vehicle dynamic response signals.
  • the driving environment intelligent sensing module acquires road surface information and driving behavior signals of the preceding vehicle based on road surface measurement signals and vehicle distance signals.
  • the vehicle state response information estimation module obtains vehicle state information based on road surface information and vehicle dynamic response signals.
  • the power control module sends a throttle opening signal to the power system and a brake pressure signal to the braking system based on the optimal cruising speed.
  • a vehicle including the above-mentioned adaptive cruise system.
  • a control method for an adaptive cruise system specifically:
  • the adaptive cruise control sub-module determines the expected root mean square value of the weighted acceleration of the body center of mass based on the set target comfort level, and calculates the optimal cruising speed based on the expected root mean square value of the weighted acceleration of the body center of mass and the current driving road surface information.
  • the suspension control submodule determines the current vehicle dynamics performance requirements based on the current driving speed and road surface information. Based on the current vehicle dynamics performance requirements, it switches the corresponding controllable suspension control parameters. According to the adopted control strategy, controllable suspension control Parameters and current vehicle status information, calculate the ideal suspension control force, send control signals to the vehicle suspension system, track the ideal suspension control force, and perform vibration suppression.
  • the simulation obtains the root mean square value of the weighted acceleration of the body center of mass under different road excitations and different driving speeds, and the functional relationship between the root mean square value of the weighted acceleration of the body center of mass and the driving speed under different driving conditions is obtained by fitting, which is the calculation of the ideal cruising speed. formula;
  • the risk of hitting the limit block is determined by the following method: if the root mean square value of the suspension's dynamic stroke exceeds one-third of the maximum working stroke, then there is a 99.7% probability that the suspension will hit the limit block, and ideal cruise needs to be carried out The vehicle speed will be compensated; otherwise, the vehicle speed will not be compensated.
  • the risk of jumping off the ground is determined by the following method: if the root mean square value of the wheel's dynamic load exceeds one-third of the wheel's static load, there is a 99.7% probability that the wheel will jump off the ground, and the ideal cruising speed needs to be compensated ; Otherwise, the vehicle speed will not be compensated.
  • rms(F d_i ) and rms(f d_i ) are the root mean square values of the dynamic load of each wheel and the dynamic stroke of the suspension respectively
  • F start_i is the static load of each wheel
  • f max is the maximum working stroke of the suspension
  • v ideal is the ideal cruising speed.
  • controllable suspension control parameters are determined by:
  • the comprehensive performance evaluation function takes into account both vehicle ride comfort and handling stability. ;
  • w 1 and w 2 are the weight coefficients of ride comfort and handling stability respectively, and rms(F d ) are respectively the average weighted acceleration of the body center of mass and the root mean square value of the four wheel dynamic loads, and rms(F df ) are the relevant values of the reference passive suspension.
  • the vehicle dynamics performance requirements under different driving conditions are specifically: when the vehicle is traveling at a speed greater than or equal to 90km/h, the vehicle dynamics performance requirements are handling stability; when the vehicle is traveling at a speed of less than 30km/h When traveling at a certain speed, the vehicle dynamics performance requirement is ride comfort.
  • control strategy includes a model predictive control strategy, a linear quadratic optimal control strategy or an improved ceiling control strategy.
  • the priority of vehicle dynamic performance requirements is higher than the priority of comfort requirements.
  • the present invention uses the adaptive cruise control sub-module to calculate the optimal cruising speed.
  • the suspension control sub-module switches the corresponding controllable suspension control parameters according to the real-time dynamic performance requirements of the vehicle.
  • the adaptive cruise and controllable suspension are collaboratively controlled based on the frame control parameters, effectively improving the ride comfort and handling stability issues caused by the driver's subjective behavior during the cruise speed setting process;
  • the present invention determines the expected root mean square value of the weighted acceleration of the body center of mass based on the set target comfort level, and calculates the optimal cruising speed based on the expected root mean square value of the weighted acceleration of the body center of mass and the current driving road surface information to ensure vehicle cruising.
  • the present invention determines whether to compensate for the ideal cruising speed by judging the risk of the suspension hitting the limit block or the wheel jumping off the ground. It can improve the vehicle ride as much as possible while ensuring vehicle safety and handling stability. comfort;
  • the present invention designs a comprehensive performance evaluation function that represents different vehicle dynamic performance.
  • the comprehensive performance evaluation function is used as the fitness function, and an optimization algorithm is used to perform optimization to obtain suspension control parameters under different vehicle dynamic performance requirements; different Vehicle dynamics performance requirements under driving conditions (vehicle speed and road surface) are different. Based on optimized control parameters, the vehicle suspension system can be targeted and controlled according to actual driving conditions to achieve vertical integration of vehicles under different driving conditions. Best performance;
  • the sensor module of the present invention includes a body acceleration sensor, a wheel acceleration sensor and a binocular camera; the body acceleration sensor obtains the body acceleration, the wheel acceleration sensor obtains the wheel acceleration, and the body acceleration and wheel acceleration are used to estimate the state variables during vehicle driving. , the state variables are combined with the controllable suspension control parameters to calculate the ideal suspension control force; the binocular camera collects the current driving road surface information and is used to analyze the vehicle's real-time dynamic performance requirements, and can obtain the road surface information in front of the vehicle in advance. On this basis The suspension control is real-time control, and the control effect is remarkable;
  • the adaptive cruise control instructions of the present invention include intelligent cruise speed setting instructions.
  • the cruise speed intelligent setting instructions are given, the intelligent cruise speed is selected and the optimal cruise speed and ideal suspension control force are determined.
  • Cruise which enables independent selection of vehicle comfort during adaptive cruise;
  • the present invention determines the risk of the suspension hitting the limit block or the wheel jumping off the ground based on the "3 ⁇ principle" in the random process theory.
  • the risk judgment obtained by this method has high credibility, with 99.7% credibility.
  • the present invention calculates the vehicle speed compensation amount based on the suspension dynamic stroke and wheel dynamic load root mean square value at the current vehicle speed to obtain the optimal cruising vehicle speed. Through vehicle speed compensation, the safety and safety of the vehicle during the adaptive cruise process can be ensured. handling stability;
  • the present invention designs a comprehensive performance evaluation function that represents different vehicle performance.
  • the comprehensive performance evaluation function is used as the fitness function parameter optimization range, and a genetic algorithm is used to evaluate the suspension control parameters under each driving state. Search for optimization and obtain the optimized control parameters. Based on the optimized control parameters, the vehicle suspension system can be targeted and controlled according to the actual driving conditions to achieve the optimal vertical comprehensive performance of the vehicle under different driving conditions;
  • the vehicle dynamic performance requirements under different driving conditions in the present invention are specifically: when the vehicle is traveling at high speed on a flat road When the vehicle is on a smooth road, the vehicle dynamics performance requirement is handling stability; when the vehicle is driving on a bad road, the vehicle dynamics performance requirement is ride comfort; through precise division of performance requirements, different driving conditions (vehicle speed and road surface) can be determined ), providing a reasonable basis for the optimization of suspension control parameters.
  • Figure 1 is a schematic diagram of the architecture of the adaptive cruise system according to the present invention.
  • Figure 2 is a flow chart of the adaptive cruise cooperative control method according to the present invention.
  • Figure 3 is a flow chart of the calculation method of the optimal cruising speed according to the present invention.
  • Figure 4 is an optimization flow chart of controllable suspension control parameters according to the present invention.
  • Figure 5 is a graph showing the relationship between the root mean square value of the weighted acceleration of the body center of mass and the vehicle speed under various driving conditions according to the present invention
  • Figure 6 is a graph showing the relationship between vehicle speed and the root mean square value of weighted acceleration of the body center of mass obtained by fitting according to the present invention.
  • an adaptive cruise system provided by an embodiment of the present invention includes a vehicle sensor module, a driving environment intelligent perception module, a vehicle state response information estimation module, an adaptive cruise and controllable suspension collaborative control module and a power module.
  • Control module; the adaptive cruise and controllable suspension collaborative control module are respectively connected to the vehicle sensor module, the driving environment intelligent perception module, the vehicle state response information estimation module and the power control module.
  • the vehicle sensor module is used to collect vehicle-related data needed to serve road surface information identification, vehicle state response information estimation, and adaptive cruise and controllable suspension collaborative control.
  • the vehicle sensor module includes a vehicle body acceleration sensor, a wheel acceleration sensor, a binocular camera, a millimeter wave radar, a brake pedal sensor, a brake pressure sensor and an engine speed sensor.
  • the driving environment intelligent perception module recognizes road surface information based on binocular cameras and identifies the driving status of the vehicle in front based on millimeter wave radar, and transfers relevant information to the vehicle state response information estimation module, adaptive cruise and controllable suspension collaborative control module, and provides vehicle State variable estimation, adaptive cruise and controllable suspension collaborative control provide data support.
  • the vehicle state response information estimation module is based on the signals of the vehicle body acceleration sensor and wheel acceleration sensor (i.e. vehicle Dynamic response signal), as well as the road surface information output by the intelligent sensing module of the driving environment, estimate the state information of the vehicle in real time during driving, and provide front-end information for the adaptive cruise and controllable suspension collaborative control module.
  • vehicle Dynamic response signal i.e. vehicle Dynamic response signal
  • the adaptive cruise and controllable suspension collaborative control module consists of two sub-modules: the adaptive cruise control module and the suspension control module.
  • the adaptive cruise control sub-module is used to process the adaptive cruise control instructions issued by the driver and perform adaptive Calculation of the optimal cruise speed during the intelligent setting of cruise speed;
  • the suspension control submodule is used to issue output force control instructions to the suspension system based on the vehicle dynamics performance requirements and driver comfort requirements during vehicle driving.
  • Vehicle dynamics Performance requirements have a higher priority than driver comfort requirements, and vehicle dynamics performance requirements are determined based on driving road surface information and vehicle speed.
  • the adaptive cruise control instructions issued by the driver include adaptive cruise start instructions, adaptive cruise termination instructions, cruise speed manual setting instructions, and cruise speed intelligent setting instructions.
  • the power control module is used to calculate the optimal cruise speed given by the adaptive cruise control sub-module in the adaptive cruise and controllable suspension collaborative control module, the brake pressure collected in real time by the brake pressure sensor, and the engine speed collected in real time by the engine speed sensor. rotation speed, respectively sending throttle opening control commands to the power system and brake pressure control commands to the braking system.
  • the vehicle sensor module sends the vehicle speed and brake pedal signals (collected by the brake pedal sensor) to the adaptive cruise and controllable suspension cooperative control module, and sends the vehicle speed and brake pedal signals (collected by the brake pedal sensor) to the driving environment.
  • the intelligent sensing module sends road surface measurement signals and vehicle distance signals, and sends vehicle dynamic response signals to the vehicle state response information estimation module.
  • the driving environment intelligent sensing module sends road surface information signals to the vehicle state response information estimation module, and to adaptive cruise and controllable
  • the suspension cooperative control module sends road information signals and driving behavior signals of the vehicle in front.
  • the vehicle state response information estimation module sends vehicle state information to the adaptive cruise and controllable suspension cooperative control module.
  • the adaptive cruise and controllable suspension cooperative control module It sends the optimal cruise speed signal and the target control force signal to the suspension system respectively to the power control module.
  • the power control module sends the throttle opening signal to the power system and the brake pressure signal to the braking system respectively.
  • the adaptive cruise and controllable suspension system of the embodiment of the present invention through the setting of the adaptive cruise and controllable suspension collaborative control module, is based on the vehicle speed requirements of the adaptive cruise control sub-module and the control force requirements of the suspension control sub-module. , issuing control instructions to the power system, braking system and suspension system respectively.
  • the vehicle vertical dynamic performance during the adaptive cruise process is improved through cooperative control of adaptive cruise and controllable suspension. .
  • embodiments of the present invention also provide a collaborative control method for the adaptive cruise system.
  • the process is shown in Figure 2, and specifically includes the following steps:
  • Step 1) when the vehicle is driving on the road, the adaptive cruise control mode is turned on, and the adaptive cruise control sub-module receives the driver's control signal. If the driver chooses to manually set the cruise speed, go to step 2) and step 10); if The driver selects intelligently set cruise speed and goes to step 7);
  • Step 2 if the vehicle in front is traveling at a constant speed, the power control module sends a control signal to the power system to maintain the current engine throttle opening and maintain a safe distance from the vehicle in front. Go to step 6); if the vehicle in front is not traveling at a constant speed, go to step 6). Go to step 3);
  • Step 3 if the vehicle in front decelerates, the power control module sends control signals to the power system and braking system respectively, uniformly reduces the engine throttle opening and increases braking pressure, and adjusts the current vehicle speed to maintain a safe distance from the vehicle in front. Go to step 6); if the vehicle in front accelerates, go to step 4);
  • Step 4 if the current driving speed is consistent with the driver's set cruise speed, the power control module sends a control signal to the power system to maintain the current engine throttle opening, and go to step 6); if the current driving speed is consistent with the driver's set cruise speed, If the cruising speed is inconsistent, go to step 5);
  • Step 5 if the current driving speed is greater than the driver's set cruise speed, the power control module sends a control signal to the power system to evenly reduce the engine throttle opening, and go to step 6); if the current driving speed is lower than the driver's set speed, If the vehicle speed is cruising, the power control module sends a control signal to the power system, evenly increases the engine throttle opening, and goes to step 6);
  • Step 6 if the driver does not choose to exit the adaptive cruise control mode, go to step 2), otherwise the adaptive cruise control sub-module accepts the driver's control signal (brake pedal signal) and exits this service;
  • Step 7 the adaptive cruise control sub-module in the adaptive cruise and controllable suspension collaborative control module determines the desired root mean square value of the weighted acceleration of the body center of mass based on the target comfort level set by the driver, and then go to step 8);
  • Step 8 the adaptive cruise control sub-module in the adaptive cruise and controllable suspension cooperative control module determines the current driving road surface information based on the road surface information recognized by the binocular camera in the sensor module, and go to step 9) and step 10);
  • Step 9 the adaptive cruise control sub-module in the adaptive cruise and controllable suspension collaborative control module calculates the optimal cruise speed based on the expected weighted root mean square acceleration of the body center of mass and the current driving road surface information, and then goes to step 2);
  • Step 10 the suspension control submodule in the adaptive cruise and controllable suspension collaborative control module determines the current vehicle dynamics performance requirements based on the current driving speed and road surface information, and then goes to step 11);
  • Step 11 the suspension control submodule in the adaptive cruise and controllable suspension collaborative control module switches the corresponding controllable suspension control parameters according to the current vehicle dynamics performance requirements, and then goes to step 12);
  • Step 12 the suspension control sub-module in the adaptive cruise and controllable suspension collaborative control module is based on the adopted control strategy (such as model predictive control strategy, linear quadratic optimal control strategy, improved ceiling control strategy, etc.) and to steps
  • the controllable suspension control parameters determined in 11) are combined with the current vehicle status information to calculate the ideal suspension control force and go to step 13);
  • Step 13 the suspension control sub-module in the adaptive cruise and controllable suspension collaborative control module sends a control signal to the vehicle suspension system, tracks the ideal suspension control force, and performs vibration suppression, go to step 14);
  • Step 14 if the trip is not over, go to step 10), otherwise end the service.
  • the priority of the control instruction based on the driving behavior of the preceding vehicle is greater than the priority of the control instruction based on the current vehicle driving state.
  • Figure 3 shows a flow chart of a method for calculating optimal cruising speed provided by an embodiment of the present invention, which specifically includes the following steps:
  • Step 1) divide the comfort level according to the root mean square value of the weighted acceleration of the body center of mass, and go to step 2); in the real-time example of the present invention, the mapping relationship between the root mean square value of the weighted acceleration of the body center of mass and the comfort level is determined according to the international standard ISO 2631 As shown in Table 1:
  • Step 2) construct road excitation models under different driving conditions, and go to step 3); the embodiment of the present invention divides different driving roads according to the road roughness grade, taking the common three grade road surfaces of A, B, and C as an example.
  • the filtered white noise method is first used to construct a single-wheel road excitation model, and then based on this basis, a four-wheel road excitation model is constructed based on the coherence principle of road excitation on both sides of the left and right wheels and the wheelbase delay principle of front and rear axle road excitation. (It is an existing technology).
  • f 0 is the lower cutoff frequency, generally its value is 0.011Hz
  • n 0 is the reference spatial frequency
  • n 0 0.1m -1
  • w(t) is the white noise random signal in the time domain
  • z r (t) is The road surface roughness signal (pavement vertical displacement signal) in the time domain
  • v is the driving speed
  • G q (n 0 ) is the road surface roughness coefficient, the specific values are shown in Table 2;
  • Step 3 construct a reference model of the vehicle's passive suspension system, and go to step 4); the embodiment of the present invention takes the linearized vehicle's passive suspension system as an example.
  • the vehicle's center of mass motion differential equation is:
  • the suspension force includes spring force and damping force:
  • Step 4 use dynamics simulation software to simulate the dynamic performance of the vehicle's passive suspension under different driving surfaces and vehicle speeds.
  • the simulation time is set to 5s, and the weighted acceleration of the body center of mass, suspension dynamic stroke and wheel dynamic load root mean square value under different driving conditions on each driving road surface are obtained, and go to step 5);
  • Step 5 according to the simulation results, draw the relationship curve of the root mean square value of the weighted acceleration of the body center of mass with the vehicle speed under different driving conditions.
  • the root mean square value of the weighted acceleration of the body center of mass with the vehicle speed under each driving condition is obtained.
  • the change curve is shown in Figure 5, go to step 6);
  • Step 6 fit the above relationship curve, and obtain the comparison between the fitting curve and the simulation curve, as shown in Figure 6, as well as the variation function of the vehicle speed with the root mean square value of the weighted acceleration of the body center of mass in each driving condition, go to step 7);
  • the function of vehicle speed changing with the root mean square value of weighted acceleration of the body center of mass is the comfort-oriented ideal cruising speed calculation formula in the embodiment of the present invention, as shown in Table 4;
  • Step 7 based on the identified road condition information, determine the change function of the body center of mass weighted acceleration root mean square value with vehicle speed on the corresponding road surface, and combine it with the expected body mass center of mass weighted acceleration root mean square value under the comfort level set by the driver to calculate Ideal cruising speed, go to step 8);
  • Step 8 substitute the ideal cruise speed into the simulation model (vehicle passive suspension system reference model), simulate the dynamic travel of each suspension and the root mean square value of the wheel dynamic load under the driving condition, and determine the dynamic travel of each suspension. and whether the root mean square value of the wheel dynamic load exceeds the boundary. If either of the two exceeds the boundary, go to step 9), otherwise go to step 10); in the embodiment of the present invention, the dynamic stroke of each suspension and the wheel dynamic load
  • the boundary value of the load root mean square value is determined based on the "3 ⁇ principle" in the stochastic process theory, that is, the root mean square value of each suspension dynamic stroke or wheel dynamic load exceeds one-third of the maximum working stroke of the suspension or the static load of the wheel. , then there is a 99.7% probability that the suspension will hit the limit block, and there is a 99.7% probability that the wheel will jump off the ground. From this, the corresponding boundaries are determined as follows;
  • rms(f d_i ) is the root mean square value of the dynamic stroke of each suspension
  • f max is the maximum working stroke of the suspension
  • rms(F d_i ) is the root mean square value of the dynamic load of each wheel
  • Step 9 based on the suspension dynamic stroke and wheel dynamic load root mean square value at the current vehicle speed, calculate the vehicle speed compensation amount to obtain the optimal cruising speed and go to step 10); the specific calculation method is as follows:
  • Step 10 output the optimal cruising speed.
  • Figure 4 shows a flow chart of a controllable suspension control parameter optimization method provided by an embodiment of the present invention.
  • the controllable suspension system uses a magnetorheological damper with adjustable damping as an actuator.
  • Using the improved ceiling control strategy to control the suspension for vibration suppression includes the following steps:
  • Step 1) combine the driving road surface information and vehicle speed to analyze the vehicle dynamic performance under different driving conditions, obtain the suspension control targets under each driving state, and go to step 2);
  • the specific control targets determined in the embodiment of the present invention are as follows As shown in Table 5;
  • Step 2) according to different suspension control targets, design a comprehensive performance evaluation function that represents different performances of the vehicle, and go to step 3);
  • the comprehensive performance evaluation function designed in the embodiment of the present invention is as follows:
  • w 1 and w 2 are the weight coefficients of ride comfort and handling stability respectively, and rms(F d ) are respectively the average weighted acceleration of the body center of mass and the root mean square value of the four wheel dynamic loads, and rms(F df ) are the relevant values of the reference passive suspension.
  • the weight coefficients under different control objectives are obtained as shown in Table 6;
  • Step 3 construct the road excitation model under different driving conditions, use the same modeling method as in the optimal cruise speed calculation process, and go to step 4);
  • Step 4 build a vehicle magnetorheological semi-active suspension model including magnetorheological dampers (belonging to the vehicle controllable suspension system One type of model), go to step 5);
  • a seven-degree-of-freedom model of the entire vehicle is used to optimize the controllable suspension control parameters.
  • the differential equation of the center of mass motion of the magnetorheological semi-active suspension model of the entire vehicle is as follows Shown:
  • the suspension force includes the spring force and the actuator force:
  • c pi is the passive damping coefficient
  • c si is the ceiling damping coefficient
  • c min is the minimum damping coefficient of the magnetorheological damper.
  • c min is 700N ⁇ s/m
  • the front and rear suspensions are respectively Using the same control parameters, the control parameters that need to be determined in the embodiment of the present invention include two groups, namely front suspension control parameters (c p1 , c s1 ) and rear suspension control parameters (c p2 , c s2 );
  • Step 5 according to the external characteristic parameters of the magnetorheological damper used in the embodiment of the present invention, determine the optimization range of the control parameters as 700N ⁇ s/m ⁇ c pi ⁇ 2000N ⁇ s/m and 1000N ⁇ s/m respectively ⁇ c si ⁇ 4000N ⁇ s/m, go to step 6);
  • Step 6 the embodiment of the present invention uses the comprehensive performance evaluation function designed in step 2) as the fitness function. 5) Within the determined parameter optimization range, use a genetic algorithm to optimize the suspension control parameters under each driving state, obtain the optimized control parameters, and go to step 7);
  • Step 7 substitute the optimized control parameters into the simulation model (vehicle magnetorheological semi-active suspension model) to verify the dynamic performance. If the comprehensive performance is optimized, go to step 8), otherwise go to step 6) ;
  • Step 8 construct the suspension optimal control parameter set.
  • the control parameters optimized in the embodiment of the present invention are shown in Table 7.

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Abstract

一种协同控制模块、自适应巡航系统及其控制方法、交通工具,自适应巡航系统包括车辆传感器模块、行车环境智能感知模块、车辆状态响应估计模块、自适应巡航与可控悬架协同控制模块、动力学控制模块;自适应巡航的控制方法为:根据驾驶员设定的巡航车速进行自适应巡航,或根据驾驶员设定的巡航舒适性等级,由自适应巡航与可控悬架系统依据行驶工况与驾驶员需求智能计算最优巡航车速,实现自适应巡航,巡航过程中对可控悬架进行协同控制,依据不同行驶工况下的车辆性能需求自适应地切换悬架控制参数。协同控制模块能够实现自适应巡航与可控悬架协同控制,在保证车辆安全性的基础上有效改善车辆自适应巡航过程中的乘坐舒适性。

Description

一种协同控制模块、自适应巡航系统及其控制方法、交通工具 技术领域
本发明属于辅助驾驶和车辆底盘动力学控制技术领域,具体涉及一种自适应巡航系统及其控制方法。
背景技术
自适应巡航是当前车辆行驶过程中一种重要的智能化辅助系统,能够大幅降低长途驾驶的疲劳感,为驾驶员提供更轻松舒适的驾驶体验。巡航控制实际上指的就是车速控制,属于车辆纵向动力学控制。当前关于自适应巡航控制的研究主要在集中在车速跟踪和避障上,鲜有研究考虑巡航过程中车辆的乘坐舒适性与操纵稳定性。车辆乘坐舒适性与操纵稳定性涉及垂向动力学控制,可控悬架系统虽然可以通过半主动/主动控制来改善车辆行驶过程中的垂向动力学性能,但控制效果受到行驶车速的影响较大。相同行驶路面下,较高的行驶车速将导致较差的乘坐舒适性与操纵稳定性。如何协调自适应巡航与可控悬架控制,通过纵垂向协同控制提高巡航过程中的车辆垂向动力学性能,当前研究未能给出有效解决办法。
发明内容
针对现有技术中存在不足,本发明提供了一种自适应巡航系统及其控制方法,有效提高车辆巡航过程中的垂向动力学性能。
本发明是通过以下技术手段实现上述技术目的的。
一种自适应巡航与可控悬架协同控制模块,包括自适应巡航控制子模块与悬架控制子模块;
所述自适应巡航控制子模块用于处理自适应巡航控制指令,所述自适应巡航控制指令包括巡航车速智能设置指令,在巡航车速智能设置过程中计算最优巡航车速;
所述悬架控制子模块根据车辆实时动力学性能需求,切换对应的可控悬架控制参数。
上述技术方案中,所述自适应巡航控制子模块由设定的目标舒适性等级确定期望车身质心加权加速度均方根值,结合当前行驶路面信息,计算最优巡航车速。
上述技术方案中,所述可控悬架控制参数是通过方式确定的:
结合行驶路面信息和车速,判断不同行驶工况下的车辆动力学性能需求,并设计表征不同车辆动力学性能的综合性能评价函数,所述综合性能评价函数同时考虑车辆乘坐舒适性与操纵稳定性;
以综合性能评价函数为适应度函数,采用优化算法进行寻优,得到不同车辆动力学性能 需求下的悬架控制参数。
一种自适应巡航系统,包括上述协同控制模块。
上述技术方案中,所述自适应巡航与可控悬架协同控制模块接收传感器模块的信号、行车环境智能感知模块和车辆状态响应信息估计模块的信号,并将最优巡航车速发送给动力控制模块。
上述技术方案中,所述车辆传感器模块用于获取车速和制动踏板信号、路面测量信号和车距信号、车辆动态响应信号。
上述技术方案中,所述行车环境智能感知模块基于路面测量信号和车距信号,获取路面信息以及前车驾驶行为信号。
上述技术方案中,所述车辆状态响应信息估计模块基于路面信息和车辆动态响应信号,获取车辆状态信息。
上述技术方案中,所述动力控制模块基于最优巡航车速,向动力系统发出油门开度信号、向制动系统发出制动压力信号。
一种交通工具,包括上述自适应巡航系统。
一种自适应巡航系统的控制方法,具体为:
自适应巡航控制子模块由设定的目标舒适性等级确定期望的车身质心加权加速度均方根值,根据期望车身质心加权加速度均方根值以及当前行驶路面信息,计算最优巡航车速。
进一步地,还包括:
悬架控制子模块依据当前行驶车速与路面信息,确定当前车辆动力学性能需求,基于当前车辆动力学性能需求,切换对应的可控悬架控制参数,根据采用的控制策略、可控悬架控制参数及当前车辆状态信息,计算理想悬架控制力,并向车辆悬架系统发出控制信号,跟踪理想悬架控制力,进行振动抑制。
进一步地,所述最优巡航车速通过以下方法获得:
仿真获取不同路面激励、不同行驶车速下的车身质心加权加速度均方根值,拟合得到不同行驶工况下车身质心加权加速度均方根值与行驶车速之间的函数关系,即理想巡航车速计算公式;
根据路面信息选择相应路面下的理想巡航车速计算公式,再依据驾驶员选择的乘坐舒适性等级确定期望的车身质心加权加速度均方根值,代入选择的理想巡航车速计算公式计算得到理想巡航车速;
将理想巡航车速代入仿真模型,得到行驶工况下的悬架动行程与车轮动载荷均方根值,如果存在撞击限位块或跳离地面风险,对理想巡航车速进行补偿,得到最优巡航车速。
进一步地,所述撞击限位块风险通过以下方法确定:若悬架动行程均方根值超过最大工作行程的三分之一,则悬架存在99.7%概率撞击限位块,需要对理想巡航车速进行补偿;反之,不对车速进行补偿。
更进一步地,所述跳离地面风险通过以下方法确定:若车轮动载荷均方根值超过车轮静载荷的三分之一,则车轮存在99.7%概率跳离地面,需要对理想巡航车速进行补偿;反之,不对车速进行补偿。
更进一步地,所述对理想巡航车速的补偿通过以下方法实现:
式中,rms(Fd_i)和rms(fd_i)分别为各车轮动载荷与悬架动行程均方根值,Fstart_i为各车轮静载荷,fmax为悬架最大工作行程,i=1、2、3、4,分别对应四个车轮,v理想是理想巡航车速。
进一步地,所述可控悬架控制参数是通过方式确定的:
结合行驶路面信息和车速,判断不同行驶工况下的车辆动力学性能需求,并设计表征不同车辆动力学性能的综合性能评价函数,所述综合性能评价函数同时考虑车辆乘坐舒适性与操纵稳定性;
以综合性能评价函数P为适应度函数,采用优化算法进行寻优,得到不同车辆动力学性能需求下的悬架控制参数。
更进一步地,所述综合性能评价函数P的表达式为:
式中,w1和w2分别为乘坐舒适性和操纵稳定性的权重系数,和rms(Fd)分别为车身质心加权加速度与四个车轮动载荷均方根值的平均值,和rms(Fdf)为参考被动悬架的相关值。
更进一步地,所述不同行驶工况下的车辆动力学性能需求具体为:当车辆以大于等于90km/h的速度行驶时,车辆动力学性能需求为操纵稳定性;当车辆以小于30km/h的速度行驶时,车辆动力学性能需求为乘坐舒适性。
进一步地,所述控制策略包括模型预测控制策略、线性二次最优控制策略或改进天棚控制策略。
进一步地,车辆动力学性能需求的优先级高于舒适性需求的优先级。
本发明的有益效果为:
(1)本发明由自适应巡航控制子模块计算最优巡航车速,悬架控制子模块根据车辆实时动力学性能需求,切换对应的可控悬架控制参数,根据最优巡航车速和可控悬架控制参数进行自适应巡航与可控悬架协同控制,有效改善巡航速度设定过程中因驾驶员主观行为带来的乘坐舒适性和操纵稳定性问题;
(2)本发明由设定的目标舒适性等级确定期望的车身质心加权加速度均方根值,根据期望车身质心加权加速度均方根值以及当前行驶路面信息,计算最优巡航车速,保证车辆巡航过程中的垂向动力学性能;
(3)本发明通过判断悬架撞击限位块或车轮跳离地面的风险,确定是否对理想巡航车速进行补偿,可以在确保车辆安全性与操纵稳定性的前提下,尽可能地提高车辆乘坐舒适性;
(4)本发明设计表征不同车辆动力学性能的综合性能评价函数,以综合性能评价函数为适应度函数,采用优化算法进行寻优,得到不同车辆动力学性能需求下的悬架控制参数;不同行驶工况(车速与路面)下的车辆动力学性能需求不同,基于优化的控制参数,可以根据实际行驶工况对车辆悬架系统进行针对性控制,实现不同行驶工况下的车辆垂向综合性能最优;
(5)本发明的传感器模块包括车身加速度传感器、车轮加速度传感器和双目摄像头;车身加速度传感器获取车身加速度,车轮加速度传感器获取车轮加速度,车身加速度和车轮加速度用于估计车辆行驶过程中的状态变量,状态变量与可控悬架控制参数结合,计算理想悬架控制力;双目摄像头采集当前行驶路面信息,用于分析车辆实时动力学性能需求,可以提前获取车辆前方路面信息,在此基础上进行的悬架控制为实时控制,控制效果显著;
(6)本发明自适应巡航控制指令包括巡航车速智能设置指令,在巡航车速智能设置指令时,选择智能设定巡航车速,并确定最优巡航车速和理想悬架控制力,相比传统自适应巡航,可实现自适应巡航过程中车辆舒适性的自主选择;
(7)本发明判断悬架撞击限位块或车轮跳离地面的风险,依据随机过程理论中的“3σ原则”进行确定,以此得到的风险判断可信度高,有99.7%的可信度;
(8)本发明依据当前车速下的悬架动行程与车轮动载荷均方根值,计算车速补偿量,得到最优巡航车速,通过车速补偿,可以确保自适应巡航过程中车辆的安全性与操纵稳定性;
(9)本发明针对不同悬架控制目标,设计表征车辆不同性能的综合性能评价函数,综合性能评价函数作为适应度函数参数优化范围中,采用遗传算法对各行驶状态下的悬架控制参数进行寻优,得到优化后的控制参数,基于优化的控制参数,可以根据实际行驶工况对车辆悬架系统进行针对性控制,实现不同行驶工况下的车辆垂向综合性能最优;
(10)本发明中不同行驶工况下的车辆动力学性能需求具体为:当车辆以高速行驶在平 坦路面上时,车辆动力学性能需求为操纵稳定性;当车辆行驶在恶劣路面上时,车辆动力学性能需求为乘坐舒适性;通过性能需求精确划分,可以确定不同行驶工况(车速与路面)下的悬架控制目标,为悬架控制参数优化提供合理依据。
附图说明
为了更清楚地说明本发明实施例中的技术方案,下面将对实施例描述中所需要使用的附图作简单的介绍,显而易见地,下面描述中的附图仅仅是本发明的一些实施例,对于本领域普通技术人员来讲,在不付出创造性劳动的前提下,还可以根据这些附图获得其他的附图。
图1为本发明所述自适应巡航系统架构示意图;
图2为本发明所述自适应巡航协同控制方法流程图;
图3为本发明所述最优巡航车速的计算方法流程图;
图4为本发明所述可控悬架控制参数的优化流程图;
图5为本发明所述各行驶路况下车身质心加权加速度均方根值随车速的变化关系曲线图;
图6为本发明所述拟合得到的车速随车身质心加权加速度均方根值的变化关系曲线图。
具体实施方式
为使本发明实施例的目的、技术方案和优点更加清楚,下面将结合本发明实施例中的附图,对发明实施例中的技术方案作进一步的说明,显然,所描述的实施例是本发明的一部分实施例,而不是全部实施例。基于本发明中的实施例,本领域普通技术人员在没有做出创造性劳动的前提下所获得的所有其他实施例都属于本发明保护的范围。
如图1所示,本发明实施例提供的一种自适应巡航系统,包括车辆传感器模块、行车环境智能感知模块、车辆状态响应信息估计模块、自适应巡航与可控悬架协同控制模块和动力控制模块;所述自适应巡航与可控悬架协同控制模块分别与所述车辆传感器模块、行车环境智能感知模块、车辆状态响应信息估计模块以及动力控制模块相连。
车辆传感器模块用于采集服务于路面信息识别、车辆状态响应信息估计以及自适应巡航与可控悬架协同控制所需车辆相关数据。本发明实施例中,车辆传感器模块包括车身加速度传感器、车轮加速度传感器、双目摄像头、毫米波雷达、制动踏板传感器、制动压力传感器和发动机转速传感器。
行车环境智能感知模块基于双目摄像头识别路面信息、基于毫米波雷达识别前车行驶状态,并将相关信息传递给车辆状态响应信息估计模块、自适应巡航与可控悬架协同控制模块,为车辆状态变量估计、自适应巡航与可控悬架协同控制提供数据支持。
车辆状态响应信息估计模块基于车身加速度传感器与车轮加速度传感器的信号(即车辆 动态响应信号),以及行车环境智能感知模块输出的路面信息,实时估计车辆行驶过程中的状态信息,为自适应巡航与可控悬架协同控制模块提供前端信息。
自适应巡航与可控悬架协同控制模块由自适应巡航控制模块与悬架控制模块两个子模块组成,自适应巡航控制子模块用于处理驾驶员发出的自适应巡航控制指令,以及进行自适应巡航车速智能设置过程中最优巡航车速的计算;悬架控制子模块用于根据车辆行驶过程中的车辆动力学性能需求以及驾驶员舒适性需求向悬架系统发出输出力控制指令,车辆动力学性能需求的优先级高于驾驶员舒适性需求的优先级,车辆动力学性能需求依据行驶路面信息与车速确定。本发明实施例中,驾驶员发出的自适应巡航控制指令包括自适应巡航启动指令、自适应巡航终止指令、巡航车速手动设置指令以及巡航车速智能设置指令。
动力控制模块用于依据自适应巡航与可控悬架协同控制模块中自适应巡航控制子模块给出的最优巡航车速、制动压力传感器实时采集的制动压力、发动机转速传感器实时采集的发动机转速,分别向动力系统发出油门开度控制指令,向制动系统发出制动压力控制指令。
具体参见图1,对于本发明实施例的自适应巡航系统,车辆传感器模块向自适应巡航与可控悬架协同控制模块发送车速和制动踏板信号(通过制动踏板传感器采集)、向行车环境智能感知模块发送路面测量信号和车距信号、向车辆状态响应信息估计模块发送车辆动态响应信号,行车环境智能感知模块分别向车辆状态响应信息估计模块发送路面信息信号、向自适应巡航与可控悬架协同控制模块发送路面信息信号和前车驾驶行为信号,车辆状态响应信息估计模块向自适应巡航与可控悬架协同控制模块发送车辆状态信息,自适应巡航与可控悬架协同控制模块分别向动力控制模块发出最优巡航车速信号、向悬架系统发送目标控制力信号,动力控制模块分别向动力系统发出油门开度信号、向制动系统发出制动压力信号。
本发明实施例的自适应巡航与可控悬架系统,通过自适应巡航与可控悬架协同控制模块的设置,根据自适应巡航控制子模块的车速需求和悬架控制子模块的控制力需求,分别向动力系统、制动系统和悬架系统发出控制指令,在实现自适应巡航的基础上,通过自适应巡航与可控悬架协同控制改善自适应巡航过程中的车辆垂向动力学性能。
基于上述自适应巡航系统,本发明实施例还给出了一种自适应巡航系统的协同控制方法,其流程如图2所示,具体包括以下步骤:
步骤1),车辆在道路上行驶时,自适应巡航控制模式开启,自适应巡航控制子模块接受驾驶员控制信号,若驾驶员选择手动设定巡航车速,转步骤2)和步骤10);若驾驶员选择智能设定巡航车速,转步骤7);
步骤2),若前车匀速行驶,则动力控制模块向动力系统发出控制信号,维持当前发动机油门开度,与前车保持安全距离,转至步骤6);若前车非匀速行驶,则转至步骤3);
步骤3),若前车减速行驶,则动力控制模块分别向动力系统与制动系统发出控制信号,均匀减小发动机油门开度并增大制动压力,调整当前车速与前车保持安全距离,转至步骤6);若前车加速行驶,则转至步骤4);
步骤4),若当前行驶车速与驾驶员设定巡航车速一致,则动力控制模块向动力系统发出控制信号,维持当前发动机油门开度,转至步骤6);若当前行驶车速与驾驶员设定巡航速度不一致,转至步骤5);
步骤5),若当前行驶车速大于驾驶员设定巡航车速,则动力控制模块向动力系统发出控制信号,均匀减小发动机油门开度,转至步骤6);若当前行驶车速小于驾驶员设定巡航车速,则动力控制模块向动力系统发出控制信号,均匀增大发动机油门开度,并转至步骤6);
步骤6),若驾驶员没有选择退出自适应巡航控制模式,转至步骤2),否则自适应巡航控制子模块接受驾驶员控制信号(制动踏板信号),退出本次服务;
步骤7),自适应巡航与可控悬架协同控制模块中自适应巡航控制子模块依据驾驶员设定的目标舒适性等级确定期望的车身质心加权加速度均方根值,转至步骤8);
步骤8),自适应巡航与可控悬架协同控制模块中自适应巡航控制子模块依据传感器模块中双目摄像头识别的路面信息确定当前行驶路面信息,转至步骤9)和步骤10);
步骤9),自适应巡航与可控悬架协同控制模块中自适应巡航控制子模块根据期望车身质心加权加速度均方根值以及当前行驶路面信息,计算最优巡航车速,转至步骤2);
步骤10),自适应巡航与可控悬架协同控制模块中悬架控制子模块依据当前行驶车速与路面信息,确定当前车辆动力学性能需求,转至步骤11);
步骤11),自适应巡航与可控悬架协同控制模块中悬架控制子模块根据当前车辆动力学性能需求,切换对应的可控悬架控制参数,转至步骤12);
步骤12),自适应巡航与可控悬架协同控制模块中悬架控制子模块根据采用的控制策略(例如模型预测控制策略、线性二次最优控制策略、改进天棚控制策略等)以及至步骤11)中确定的可控悬架控制参数结合当前车辆状态信息,计算理想悬架控制力,转至步骤13);
步骤13),自适应巡航与可控悬架协同控制模块中悬架控制子模块向车辆悬架系统发出控制信号,跟踪理想悬架控制力,进行振动抑制,转至步骤14);
步骤14),若行程没有结束,转至步骤10),否则结束本次服务。
本发明一种自适应巡航与可控悬架协同控制方法中,基于前车驾驶行为的控制指令优先级大于基于当前车辆行驶状态的控制指令优先级。
图3所示为本发明实施例提供的一种最优巡航车速的计算方法流程图,具体包括以下步骤:
步骤1),依据车身质心加权加速度均方根值划分舒适性等级,转至步骤2);本发明实时例中依据国际标准ISO 2631确定车身质心加权加速度均方根值与舒适性等级的映射关系如表1所示:
表1舒适性等级与车身质心加权加速度均方根值
步骤2),构建不同行驶工况下的路面激励模型,转至步骤3);本发明实施例依据路面不平度等级划分不同行驶路面,以常见的A、B、C三种等级路面为例进行说明,首先采用滤波白噪声法进行单轮路面激励模型的构建,然后在此基础上依据左右轮两侧路面激励相干性原理以及前后轴路面激励轮距时延原理进行四轮路面激励模型的构建(为现有技术)。基于滤波白噪声法的单轮路面激励模型表达式为:其中f0为下截止频率,一般其值取为0.011Hz;n0为参考空间频率,n0=0.1m-1;w(t)为时域下白噪声随机信号;zr(t)为时域下路面不平度信号(路面垂向位移信号);v为行驶车速;Gq(n0)为路面不平度系数,具体数值见表2;
表2路面不平度等级分类标准
步骤3),构建整车被动悬架系统参考模型,转至步骤4);本发明实施例以线性化后的整车被动悬架系统为例进行说明,整车质心运动微分方程为:
各悬架簧下质量运动微分方程如下:
式中,各悬架簧上质量位移为:
式中,悬架力包括了弹簧力和阻尼力:
式中,ms为整车簧载质量;mui(i=1,2)为前后轮非簧载质量;Iθ为车身俯仰转动惯量;Iφ为车身侧倾转动惯量;a为车身质心至前轴距离;b为车身质心至后轴距离;Bf为前轮轮距;Br为后轮轮距;ci(i=1,2)为前后悬架阻尼系数;ksi(i=1,2)为前后悬架刚度;kt为轮胎刚度;θ为车身俯仰角;为车身俯仰角加速度;为车身侧倾角;为车身侧倾角加速度;zsi(i=1,2,3,4)为各悬架与车身连接处位移;zui(i=1,2,3,4)为各轮非簧载质量位移;zri(i=1,2,3,4)为各轮路面输入,本发明实施例中采用的具体参数如表3所示;FLF为左前悬架力,FRF为右前悬架力,FLR为左后悬架力,FRR为右后悬架力,zs为整车质心位移,为整车质心加速度,(i=1,2,3,4)为各悬架与车身连接处速度,为各轮非簧载质量速度;
表3整车被动悬架系统参数表
步骤4),采用动力学仿真软件进行不同行驶路面与车速下的整车被动悬架动力学性能仿 真,仿真时间设定为5s,获取各行驶路面不同行驶工况下的车身质心加权加速度、悬架动行程与车轮动载荷均方根值,转至步骤5);
步骤5),根据仿真结果,绘制不同行驶工况下车身质心加权加速度均方根值随车速的变化关系曲线,本发明实施例中得到各行驶工况下车身质心加权加速度均方根值随车速的变化曲线如图5所示,转至步骤6);
步骤6),对上述关系曲线进行拟合,得到拟合曲线与仿真曲线的对比如图6所示,以及各行驶工况下车速随车身质心加权加速度均方根值的变化函数,转至步骤7);车速随车身质心加权加速度均方根值的变化函数即本发明实施例中以舒适性为导向的理想巡航车速计算公式,如表4所示;
表4以舒适性为导向的理想巡航车速计算公式
步骤7),依据识别的路况信息,确定采用相应路面下车身质心加权加速度均方根值随车速的变化函数,结合驾驶员设定舒适性等级下的期望车身质心加权加速度均方根值,计算理想巡航车速,转至步骤8);
步骤8),将理想巡航车速代入仿真模型(整车被动悬架系统参考模型),仿真得到该行驶工况下的各悬架动行程与车轮动载荷均方根值,判断各悬架动行程与车轮动载荷均方根值是否超过边界,若两者中任意一者超出边界,则转至步骤9),否则转至步骤10);本发明实施例中,各悬架动行程与车轮动载荷均方根值的边界值依据随机过程理论中的“3σ原则”进行确定,即各悬架动行程或车轮动载荷均方根值超过悬架最大工作行程或车轮静载荷的三分之一,则悬架存在99.7%概率会撞击限位块、车轮存在99.7%概率会跳离地面,由此确定相应边界分别为;
式中,rms(fd_i)为各悬架动行程均方根值,fmax为悬架最大工作行程,rms(Fd_i)为各车轮动载荷均方根值,Fstart_i=(msi+mui)·g为车轮静载荷,msi(i=1,2,3,4)为各轮簧载质量,前/后轴左右轮簧载质量分别相等,ms1=ms2=377.5kg,ms3=ms4=312.5kg;
步骤9),依据当前车速下的悬架动行程与车轮动载荷均方根值,计算车速补偿量,得到最优巡航车速并转至步骤10);具体计算方法如下式:
式中,v理想是步骤6)中计算得到的理想巡航车速,v最优是补偿后的最优巡航车速,i=1,2,3,4分别对应四个车轮;
步骤10),输出最优巡航车速。
图4所示为本发明实施例提供的一种可控悬架控制参数优化方法的流程图,本发明实施例中可控悬架系统采用阻尼可调的磁流变阻尼器作为作动器,利用改进天棚控制策略来控制悬架进行振动抑制,包括以下步骤:
步骤1),结合行驶路面信息与车速分析不同行驶工况下的车辆动力学性能,得到各行驶状态下的悬架控制目标,转至步骤2);本发明实施例中确定的具体控制目标如表5所示;
表5不同行驶工况下的车辆动力学性能需求
步骤2),针对不同悬架控制目标,设计表征车辆不同性能的综合性能评价函数,转至步骤3);本发明实施例中设计的综合性能评价函数如下:
式中,w1和w2分别为乘坐舒适性和操纵稳定性的权重系数,和rms(Fd)分别为车身质心加权加速度与四个车轮动载荷均方根值的平均值,和rms(Fdf)为参考被动悬架的相关值,依据步骤1)确定的不同行驶工况下的车辆动力学性能需求,得到不同控制目标下的权重系数如表6所示;
表6不同控制目标下的权重系数
步骤3),构建不同行驶工况下的路面激励模型,采用与最优巡航车速计算流程中同样的建模方法,转步骤4);
步骤4),构建包含磁流变阻尼器的整车磁流变半主动悬架模型(属于整车可控悬架系统 模型的一种),转至步骤5);本发明实施例中采用整车七自由度模型进行可控悬架控制参数的优化,整车磁流变半主动悬架模型的质心运动微分方程如下所示:
各悬架簧下质量运动微分方程如下:
式中,各悬架簧上质量位移为:
式中,悬架力包括了弹簧力和作动器作用力:
式中,Fi(i=1,2,3,4)为磁流变阻尼器输出力,其他参数与被动悬架一致,则改进天棚控制下:
式中,cpi为被动阻尼系数,csi为天棚阻尼系数,cmin为磁流变阻尼器的最小阻尼系数,本发明实施例中cmin为700N·s/m,前悬和后悬分别采用相同的控制参数,则本发明实施例中需要确定的控制参数包含两组,分别为前悬控制参数(cp1,cs1)和后悬控制参数(cp2,cs2);
步骤5),根据本发明实施例中所采用磁流变阻尼器的外特性参数,确定控制参数的优化范围分别为700N·s/m≤cpi≤2000N·s/m和1000N·s/m≤csi≤4000N·s/m,转至步骤6);
步骤6),本发明实施例以步骤2)中设计的综合性能评价函数作为适应度函数,在步骤 5)确定的参数优化范围中,采用遗传算法对各行驶状态下的悬架控制参数进行寻优,得到优化后的控制参数,并转至步骤7);
步骤7),将优化后的控制参数代入仿真模型(整车磁流变半主动悬架模型),进行动力学性能验证,若综合性能得到优化,转至步骤8),否则转至步骤6);
步骤8),构建悬架最优控制参数集合,本发明实施例中优化得到的控制参数如表7所示。
表7优化后的悬架控制参数(cp1,cs1),(cp2,cs2)
所述实施例为本发明的优选的实施方式,但本发明并不限于上述实施方式,在不背离本发明的实质内容的情况下,本领域技术人员能够做出的任何显而易见的改进、替换或变型均属于本发明的保护范围。

Claims (21)

  1. 一种自适应巡航与可控悬架协同控制模块,其特征在于,包括自适应巡航控制子模块与悬架控制子模块;
    所述自适应巡航控制子模块用于处理自适应巡航控制指令,所述自适应巡航控制指令包括巡航车速智能设置指令,在巡航车速智能设置过程中计算最优巡航车速;
    所述悬架控制子模块根据车辆实时动力学性能需求,切换对应的可控悬架控制参数。
  2. 根据权利要求1所述的协同控制模块,其特征在于,所述自适应巡航控制子模块由设定的目标舒适性等级确定期望车身质心加权加速度均方根值,结合当前行驶路面信息,计算最优巡航车速。
  3. 根据权利要求1所述的协同控制模块,其特征在于,所述可控悬架控制参数是通过方式确定的:
    结合行驶路面信息和车速,判断不同行驶工况下的车辆动力学性能需求,并设计表征不同车辆动力学性能的综合性能评价函数,所述综合性能评价函数同时考虑车辆乘坐舒适性与操纵稳定性;
    以综合性能评价函数为适应度函数,采用优化算法进行寻优,得到不同车辆动力学性能需求下的悬架控制参数。
  4. 一种自适应巡航系统,其特征在于,包括权利要求1-3任一项所述的协同控制模块。
  5. 根据权利要求4所述的自适应巡航系统,其特征在于,所述自适应巡航与可控悬架协同控制模块接收传感器模块的信号、行车环境智能感知模块和车辆状态响应信息估计模块的信号,并将最优巡航车速发送给动力控制模块。
  6. 根据权利要求5所述的自适应巡航系统,其特征在于,所述车辆传感器模块用于获取车速和制动踏板信号、路面测量信号和车距信号、车辆动态响应信号。
  7. 根据权利要求6所述的自适应巡航系统,其特征在于,所述行车环境智能感知模块基于路面测量信号和车距信号,获取路面信息以及前车驾驶行为信号。
  8. 根据权利要求7所述的自适应巡航系统,其特征在于,所述车辆状态响应信息估计模块基于路面信息和车辆动态响应信号,获取车辆状态信息。
  9. 根据权利要求8所述的自适应巡航系统,其特征在于,所述动力控制模块基于最优巡航车速,向动力系统发出油门开度信号、向制动系统发出制动压力信号。
  10. 一种交通工具,其特征在于,包括权利要求4-9任一项所述的自适应巡航系统。
  11. 一种自适应巡航系统的控制方法,其特征在于:
    自适应巡航控制子模块由设定的目标舒适性等级确定期望的车身质心加权加速度均方根值,根据期望车身质心加权加速度均方根值以及当前行驶路面信息,计算最优巡航车速。
  12. 根据权利要求11所述的控制方法,其特征在于,还包括:
    悬架控制子模块依据当前行驶车速与路面信息,确定当前车辆动力学性能需求,基于当前车辆动力学性能需求,切换对应的可控悬架控制参数,根据采用的控制策略、可控悬架控制参数及当前车辆状态信息,计算理想悬架控制力,并向车辆悬架系统发出控制信号,跟踪理想悬架控制力,进行振动抑制。
  13. 根据权利要求11所述的控制方法,其特征在于,所述最优巡航车速通过以下方法获得:
    仿真获取不同路面激励、不同行驶车速下的车身质心加权加速度均方根值,拟合得到不同行驶工况下车身质心加权加速度均方根值与行驶车速之间的函数关系,即理想巡航车速计算公式;
    根据路面信息选择相应路面下的理想巡航车速计算公式,再依据驾驶员选择的乘坐舒适性等级确定期望的车身质心加权加速度均方根值,代入选择的理想巡航车速计算公式计算得到理想巡航车速;
    将理想巡航车速代入仿真模型,得到行驶工况下的悬架动行程与车轮动载荷均方根值,如果存在撞击限位块或跳离地面风险,对理想巡航车速进行补偿,得到最优巡航车速。
  14. 根据权利要求13所述的控制方法,其特征在于,所述撞击限位块风险通过以下方法确定:若悬架动行程均方根值超过最大工作行程的三分之一,则悬架存在99.7%概率撞击限位块,需要对理想巡航车速进行补偿;反之,不对车速进行补偿。
  15. 根据权利要求13所述的控制方法,其特征在于,所述跳离地面风险通过以下方法确定:若车轮动载荷均方根值超过车轮静载荷的三分之一,则车轮存在99.7%概率跳离地面,需要对理想巡航车速进行补偿;反之,不对车速进行补偿。
  16. 根据权利要求15所述的控制方法,其特征在于,所述对理想巡航车速的补偿通过以下方法实现:
    式中,rms(Fd_i)和rms(fd_i)分别为各车轮动载荷与悬架动行程均方根值,Fstart_i为各车轮静载荷,fmax为悬架最大工作行程,i=1、2、3、4,分别对应四个车轮,v理想是理想巡航车速。
  17. 根据权利要求12所述的控制方法,其特征在于,所述可控悬架控制参数是通过方式确定的:
    结合行驶路面信息和车速,判断不同行驶工况下的车辆动力学性能需求,并设计表征不同车辆动力学性能的综合性能评价函数,所述综合性能评价函数同时考虑车辆乘坐舒适性与 操纵稳定性;
    以综合性能评价函数P为适应度函数,采用优化算法进行寻优,得到不同车辆动力学性能需求下的悬架控制参数。
  18. 根据权利要求17所述的控制方法,其特征在于,所述综合性能评价函数P的表达式为:
    式中,w1和w2分别为乘坐舒适性和操纵稳定性的权重系数,和rms(Fd)分别为车身质心加权加速度与四个车轮动载荷均方根值的平均值,和rms(Fdf)为参考被动悬架的相关值。
  19. 根据权利要求17所述的控制方法,其特征在于,所述不同行驶工况下的车辆动力学性能需求具体为:当车辆以大于等于90km/h的速度行驶时,车辆动力学性能需求为操纵稳定性;当车辆以小于30km/h的速度行驶时,车辆动力学性能需求为乘坐舒适性。
  20. 根据权利要求12所述的控制方法,其特征在于,所述控制策略包括模型预测控制策略、线性二次最优控制策略或改进天棚控制策略。
  21. 根据权利要求12所述的控制方法,其特征在于,车辆动力学性能需求的优先级高于舒适性需求的优先级。
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