CN106809207A - A kind of electric vehicle load-carrying and gradient self-adaptation control method and its vehicle - Google Patents
A kind of electric vehicle load-carrying and gradient self-adaptation control method and its vehicle Download PDFInfo
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- CN106809207A CN106809207A CN201710044275.9A CN201710044275A CN106809207A CN 106809207 A CN106809207 A CN 106809207A CN 201710044275 A CN201710044275 A CN 201710044275A CN 106809207 A CN106809207 A CN 106809207A
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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
- B60W10/04—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
- 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
- B60W40/10—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
- B60W40/105—Speed
-
- 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
- B60W2510/08—Electric propulsion units
- B60W2510/083—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
- B60W2520/00—Input parameters relating to overall vehicle dynamics
- B60W2520/28—Wheel speed
-
- 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
- B60W2710/00—Output or target parameters relating to a particular sub-units
- B60W2710/08—Electric propulsion units
- B60W2710/083—Torque
Abstract
The present invention discloses the vehicle of a kind of electric vehicle load-carrying and gradient self-adaptation control method and adopting said method, including measures dynamic torque, calculate preferable name wheel speed, measure the steps such as actual wheel speed, compensation torque calculating, load-carrying and the gradient adaptation.Method of the present invention, so as to realize load-carrying and the gradient self adaptation of vehicle, makes vehicle even running by calculating the compensation moment of torsion of automotive power required input, the dynamic torque of adjustment vehicle output.The present invention makes electric vehicle more intelligent, improves the dynamic property and comfortableness of vehicle, and reduces cost, is had broad application prospects in vehicle traction/brake control art.
Description
Technical field
The present invention relates to a kind of intelligent control method of electric vehicle, and in particular to a kind of electric vehicle load-carrying and the gradient are certainly
The vehicle of adaptive control method and adopting said method, belongs to vehicle traction/brake control art.
Background technology
During the vehicle especially traveling of electric vehicle, complete vehicle quality and road gradient are influence longitudinal direction of car power
The important parameter of control is learned, therefore vehicle load also turns into vehicle traction/control for brake neck with the control technology of gradient self adaptation
One research direction in domain.
Control of the prior art to vehicle load and gradient self adaptation has larger defect：1st, acceleration transducer and
The application of more multisensor, not only influences the stability of system, also greatly increases cost.2nd, need to estimate complete vehicle quality and road surface
The gradient is higher to hardware requirement.
Document《Control Strategy for Hybrid Electric Vehicle research based on GPS》, propose to carry out the road grade of electric automobile
The method of estimation, the method depends on the GPS to carry out road gradient estimation, and the very little velocity error of GPS may result in larger slope
Degree evaluated error；The method is also needed to using more sensors, and the atmospheric pressure for especially easily being influenceed by extraneous factor is passed
Sensor, the reliability of the method is poor, and is not suitable for typically all being not equipped with the cart of GPS.
Document《The complete vehicle quality of electro-motive vehicle is estimated with road gradient》, it is proposed that the vehicle matter based on least square method
Amount and gradient method of estimation, the method are estimated based on vehicle motor output torque.The gradient and vehicle mass are tools
There is the amount of different qualities, the gradient changes comparatively fast over time, and it is a fast variable, and vehicle mass is generally once being tested
During be held essentially constant, it is a slow variable, thus, by the variable of above-mentioned two asynchronism be based on it is same
Longitudinal vehicle dynamic model estimate simultaneously that reliability is poor.
Document《Vehicle mass based on EKF is estimated with road grade》, using Kalman filter to car
Quality and the gradient of road carry out real-time online estimation, and realize the On-line Estimation to the gradient and vehicle mass, but
The method does not provide its specific applicability.
The content of the invention
For the purpose for overcoming the defect of prior art, first aspect present invention is to provide a kind of electric vehicle load-carrying and the gradient
Self-adaptation control method, makes vehicle in the state of load-carrying and slope change, changes vehicle input torque, so as to realize that vehicle is steady
Fixed operation.Specifically include following steps：
(1) dynamic torque, is measured：
Dynamic torque T*Including the first dynamic torque TrAnd/or the second dynamic torque Tp。
The first dynamic torque TrIt is vehicular electric machine moment of torsion, is provided by one or more motors, it is defeated by top level control device
Go out, the top level control device is one or more in accelerator pedal, brake pedal, active safety control system；Described first
Dynamic torque TrObtained by torque sensor detection, or the current of electric that is measured by electric machine controller and other parameters are calculated and asked
.
The second dynamic torque TpThe manpower and/or engine that are detected by torque sensor apply the letter of moment of torsion to vehicle
Number and obtain.The second dynamic torque TpImplementation can be moment of torsion and/or engine pair that driver applies to vehicle
Vehicle applies moment of torsion；A kind of acquisition modes that engine applies moment of torsion to vehicle can be obtained by throttle opening or distributive value
.
Especially, when the vehicle is pure electric vehicle, the numerical value of second dynamic torque is 0.
(2) preferable name wheel speed, is calculated：
The dynamic torque T measured by step (1)*It is calculated nominal wheel speed w ideally*。
The nominal wheel speed specific formula for calculation ideally is：
Jn=mr2+Jw
The meaning of each parameter is as follows in formula：T*：Dynamic torque, Jn：Ideally equivalent nominal rotary inertia, w*：
Ideally nominal wheel speed, m：The load-carrying that ideally wheel is shared, Jw：The rotary inertia of wheel, r：Radius of wheel.
(3) actual wheel speed, is measured：
Calculated by motor speed and directly export actual wheel speed w, it is also possible to which actual rotation is measured by external sensor
Fast w.
(4), compensation torque calculating：
By contrasting nominal wheel speed w*With actual wheel speed w, if w*It is close with w numerical value, then without calculating compensation moment of torsion；
If w*Differ larger with w, then calculate compensation torque Tmc.It is described to calculate compensation torque TmcAlgorithm be selected from pid control algorithm, mould
One or more in fuzzy control algorithm, optimal control algorithm, synovial membrane control algolithm.
Preferably, the compensation torque TmcComputing formula is：Tmc=K (w*-w)。
Wherein, K represents gain coefficient.
(5) load-carrying and the gradient are adapted to：
According to the compensation torque T that step (4) is obtainedmc, adjust motor torque output, so as to realize vehicle load-carrying and
Gradient self adaptation.
Further, in step (3), the formula that step (2) is provided can be directly utilized to calculate actual wheel speed institute
Corresponding simulation dynamic torque T, in step (4), the dynamic torque T for directly being measured by simulation dynamic torque T and step (1)*
Compare and calculate compensation torque Tmc, so as to step (2) be omitted.
The purpose of second aspect present invention is to provide a kind of load-carrying of application electric vehicle and gradient self-adaptation control method
Vehicle.The vehicle at least includes that torque request module, non-electrical power are input into detection module, controlled motor output module, are controlled
Electric vehicle module processed, data processing chip, vehicle wheel rotational speed detection module, compare gain control module.
The torque request module is used to receive top level control device feedack, the first of the device output of generation top level control
Dynamic torque Tr；The torque request module is connected with top level control device, at the same with the controlled motor output module Electricity Federation
Connect.The top level control device is one or more in accelerator pedal, brake pedal, active safety control system；Described first
Dynamic torque is vehicular electric machine moment of torsion.
The non-electrical power input detection module is connected with the torque sensor of vehicle, for being detected by torque sensor
Manpower and/or engine apply the signal of moment of torsion to vehicle, while being connected with engine control system communication, are opened by air throttle
Degree or distributive value obtain the moment of torsion that engine applies to vehicle, export the second dynamic torque Tp；The non-electrical power input detection
Module is connected with data processing chip communication, while being connected by control electric vehicle module communication with described.
The controlled motor output module is used to receive the first dynamic torque information T of torque request module generationrWith than
Compared with the compensation torque information T that gain control module is exportedmc, and export the 3rd dynamic torque Tm.The controlled motor output module
Electrically connected with the torque request module, electrically connected with the gain control module that compares；Communicated with the data processing chip
Connection, and be connected with by control electric vehicle module communication.
It is described to be used to receive dynamic torque T by control electric vehicle module*, system is controlled by the ECU for being controlled electric vehicle
System, control is travelled by control vehicle；The dynamic torque T*The 3rd power including controlled motor output module output is turned round
Square TmThe the second dynamic torque T exported with non-electrical power input detection modulep.It is described by control electric vehicle module respectively with institute
State controlled motor output module, non-electrical power input detection module communication connection.
The data processing chip is by being calculated preferable name wheel speed w*, export mould with the controlled motor respectively
Block, power input detection module communication connection, and be connected with gain control module communication is compared.
The vehicle wheel rotational speed detection module is used to measure actual wheel rotating speed w；The vehicle wheel rotational speed detection module is by outer
Portion's sensor measures actual wheel rotating speed w, or obtains actual wheel rotating speed w by motor speed calculating.The vehicle wheel rotational speed inspection
Survey module to be connected with by control electric vehicle module, be connected with gain control module communication is compared.
The gain control module that compares connects with the data processing chip, vehicle wheel rotational speed detection module communication respectively
Connect, and be connected with controlled motor output module communication；The gain control module that compares compares w in real time*The difference of-w, and
It is calculated compensation torque Tmc。
A kind of electric vehicle load-carrying of the present invention and the vehicle of gradient self-adaptation control method and adopting said method,
There is good load-carrying and gradient self adaptation effect for electric vehicle, and cost is relatively low.
The present invention has the following technical effect that：
1st, make electric vehicle more intelligent, improve the dynamic property and comfortableness of vehicle.
2nd, the extra equipment such as sensor, GPS is not increased, it is ensured that the stability of system, and reduces cost.
3rd, do not need to estimate vehicle mass and road gradient, save system hardware resources expense.
Brief description of the drawings
Fig. 1 is the flow chart of the electric vehicle load-carrying of embodiment 1 and gradient self-adaptation control method.
Fig. 2 is the principle schematic of electric vehicle load-carrying of the present invention and gradient self-adaptation control method.
Wherein, Fig. 2 a are principle schematic of the embodiment 1 with wheel speed w as comparative quantity；Fig. 2 b be embodiment 1 in, with take turns
Rotational accelerationInstead of wheel speed w as comparative quantity principle schematic；Fig. 2 c are original of the embodiment 2 with torque T as comparative quantity
Reason schematic diagram.
Fig. 3 is the wheel model force analysis of ideally vehicle.
The wheel model force analysis of vehicle when Fig. 4 is vehicle actual motion.
Fig. 5 is the hardware mould of the vehicle of the application electric vehicle load-carrying that embodiment 3 is related to and gradient self-adaptation control method
Block is constituted and its annexation schematic diagram.
Fig. 6 is the velocity profile of the vehicle load self adaptation of embodiment 5.
Fig. 7 is the moment variations figure of the vehicle load self adaptation of embodiment 5.
Fig. 8 is the velocity profile of the vehicle gradient self adaptation of embodiment 6.
Fig. 9 is the moment variations figure of the vehicle gradient self adaptation of embodiment 6.
Figure 10 is the velocity profile of vehicle load and gradient self adaptation under the extreme condition of embodiment 7.
Figure 11 is the moment variations figure of vehicle load and gradient self adaptation under the extreme condition of embodiment 7.
" without control " in Fig. 6~11 represents and control method of the present invention is not used, and " having control " represents and use hair
The bright control method being related to.
Specific embodiment
Below by specific embodiment, further technical scheme is specifically described.It should be understood that below
Embodiment be intended only as illustrating, and do not limit the scope of the invention, while those skilled in the art is according to the present invention
The obvious change and modification made are also contained within the scope of the invention.
The wheel speed that the present invention is referred to is the angular speed of motor.Wheel speed w of the present invention and nominal wheel speed w*Can
Respectively with wheel rotational accelerationWith name wheel rotational accelerationInstead of.Method of the present invention can be applied in motor-driven
Vehicle or engine motor hybrid power drive vehicle on.Vehicle of the present invention includes but is not limited to automobile, electronic
Bicycle, electric assisted bicycle etc..
Embodiment 1
As shown in Fig. 1 and Fig. 2 a, a kind of electric vehicle load-carrying and gradient self-adaptation control method are：Vehicle power is obtained to turn round
Square T*, i.e. the total driving force of vehicle, and calculate vehicle nominal wheel speed w in the ideal situation*；Obtain the reality during traveling
Border vehicle wheel rotational speed w, using nominal wheel speed w ideally*Compared with actual wheel rotating speed w, and calculate acquisition vehicle
The compensating torque T of dynamical system required inputmc, the dynamic torque T of adjustment vehicle output*, make vehicle even running.
Specifically include measure dynamic torque, calculate preferable name wheel speed, measure actual wheel speed, compensation torque calculating,
The step such as load-carrying and gradient adaptation：
(1) dynamic torque, is measured：Dynamic torque T*Including the first dynamic torque TrAnd/or the second dynamic torque Tp。
The first dynamic torque TrIt is vehicular electric machine moment of torsion, is provided by multiple motors, is exported by top level control device, by electricity
The current of electric and other parameters that machine controller is measured are calculated tries to achieve, and the top level control device is accelerator pedal and active safety control
System processed.In the present embodiment, the second dynamic torque TpIt is the moment of torsion that driver and engine apply to vehicle, driver couple
The moment of torsion that vehicle applies is applied the signal of moment of torsion by the driver that torque sensor is detected and is obtained to vehicle；Engine is applied to vehicle
Plus moment of torsion obtained by throttle opening or distributive value.
(2) preferable name wheel speed, is calculated：The dynamic torque T measured by step (1)*It is calculated ideally
Nominal wheel speed w*。
As shown in the wheel of vehicle model force analysis of Fig. 3, in the case of ignoring tyre slip, because dynamics of vehicle is closed
System, using the dynamic torque T of vehicle*And the univers parameter of vehicle tries to achieve nominal wheel speed w in the ideal case*, Fig. 3
In each parameter meaning it is as follows：T*：Dynamic torque, w*：Ideally nominal wheel speed, m：Ideally wheel is shared
Load-carrying, Jw：The rotary inertia of wheel, r：Radius of wheel.
Thus, the nominal wheel speed w ideally*Can be calculated by following equation：
Jn=mr2+Jw
J in formulanRepresent ideally equivalent nominal rotary inertia.
(3) actual wheel speed, is measured：
Fig. 4 show wheel model force analysis of the vehicle in load-carrying and the gradient of actual motion, each parameter in figure
The same Fig. 3 of meaning, the actual wheel speed w of vehicle in Fig. 4, are obtained by angular-rate sensor.
(4), compensation torque calculating：
Vehicle it is non-loaded without the gradient in the case of, w*Should be close with w values, if in the constant situation of driving force
Under, w*Significantly greater than w then may determine that load-carrying and/or the reason gradient change.Therefore, driving force T should now be adjusted*With
Make w*It is close with w, that is, increase a compensation torque Tmc, so as to realize load-carrying and gradient self adaptation.
Specifically, by contrasting nominal wheel speed w*With actual wheel speed w, if | w*- w | and ＜ 3km/h (i.e. | w*- w | ≈ 0),
Then without calculating compensation moment of torsion；If | w*- w | >=3km/h, then calculate compensation torque Tmc.It is described to calculate compensation torque TmcMeter
Calculating formula is：Tmc=K (w*-w).Wherein, K represents gain coefficient.
(5) load-carrying and the gradient are adapted to：
According to the compensation torque T that step (4) is obtainedmc, adjust motor torque output, so as to realize vehicle load-carrying and
Gradient self adaptation.
Embodiment 2
As shown in Figure 2 b, a kind of electric vehicle load-carrying and gradient self-adaptation control method, step are as follows：
(1) dynamic torque, is measured：Dynamic torque T*Including the first dynamic torque TrAnd/or the second dynamic torque Tp。
The first dynamic torque TrIt is vehicular electric machine moment of torsion, by accelerator pedal, brake pedal, active safety control system
The top level control device output of composition.The first dynamic torque TrThe current of electric and other parameters meter measured by electric machine controller
Try to achieve, the second dynamic torque TpThe driver detected by torque sensor applies the signal of moment of torsion to vehicle and starts
Machine throttle opening or distributive value, it is common to obtain.
(2) actual wheel speed, is measured：
The actual wheel speed w of vehicle is obtained by angular-rate sensor.
(3), calculating simulation dynamic torque T：
Corresponding simulation dynamic torque T is calculated by actual wheel speed w, formula is
Jn=mr2+Jw
The meaning of each parameter is as follows：T：Simulation dynamic torque, w：The actual wheel speed of vehicle, m：Ideally wheel is shared
Load-carrying, Jw：The rotary inertia of wheel, JnRepresent ideally equivalent nominal rotary inertia, r：Radius of wheel.
(4), compensation torque calculating：
The dynamic torque T measured with step (1) by the simulation dynamic torque T being calculated in step (3)*Subtraction calculations go out
Compensation torque Tmc。
(5) load-carrying and the gradient are adapted to：
According to the compensation torque T that step (4) is obtainedmc, adjust motor torque output, so as to realize vehicle load-carrying and
Gradient self adaptation.
Embodiment 3
As shown in figure 5, the vehicle of a kind of load-carrying of application electric vehicle and gradient self-adaptation control method, is used to as hardware
The method described in embodiment 1 is realized, it is at least defeated including torque request module, non-electrical power input detection module, controlled motor
Go out module, by control electric vehicle module, data processing chip, vehicle wheel rotational speed detection module, compare gain control module.
The torque request module is used to receive top level control device feedack, the first of the device output of generation top level control
Dynamic torque Tr；The top level control device is one or more in accelerator pedal, brake pedal, active safety control system；
First dynamic torque is vehicular electric machine moment of torsion.The non-electrical power input detection module is used to be examined by torque sensor
The signal that manpower and/or engine apply moment of torsion to vehicle is surveyed, while be connected with engine control system communication, by air throttle
Aperture or distributive value obtain the moment of torsion that engine applies to vehicle, export the second dynamic torque Tp；Described in the present embodiment
Two dynamic torque TpFor the moment of torsion sum that driver and engine apply to vehicle；When the vehicle is non-power-assisted pure electric vehicle
When, then the numerical value of second dynamic torque is 0.The controlled motor output module is used to receive torque request module generation
First dynamic torque information TrWith the compensation torque information T for comparing gain control module outputmc, and export the 3rd dynamic torque
Tm。
It is described to be used to receive dynamic torque T by control electric vehicle module*, and control to be travelled by control vehicle；It is described dynamic
Power torque T*The 3rd dynamic torque T including controlled motor output module outputmExported with non-electrical power input detection module
The second dynamic torque Tp。
The data processing chip is by being calculated preferable name wheel speed w*.The vehicle wheel rotational speed detection module is used for
Measure actual wheel rotating speed w；The vehicle wheel rotational speed detection module measures actual wheel rotating speed w, Huo Zheyou by external sensor
Motor speed is calculated and obtains actual wheel rotating speed w.The gain control module that compares compares w in real time*The difference of-w, and calculate
To compensation torque Tmc。
Embodiment 4
As shown in figure 5, the vehicle of a kind of load-carrying of application electric vehicle and gradient self-adaptation control method, based on embodiment 2,
The annexation of each hardware composition part is as follows：The torque request module is connected with top level control device, at the same with the control
Motor output module processed is electrically connected；The top level control device is in accelerator pedal, brake pedal, active safety control system
Plant or various；First dynamic torque is vehicular electric machine moment of torsion.The power of the non-electrical power input detection module and vehicle
Square sensor is connected, and is connected with data processing chip communication, while being connected by control electric vehicle module communication with described.
The controlled motor output module is electrically connected with the torque request module, and gain control module electricity is compared with described
Connection；It is connected with data processing chip communication, and is connected with by control electric vehicle module communication.It is described electronic by control
The ECU control systems that vehicle modules pass through controlled electric vehicle, control is travelled by control vehicle；It is defeated with the controlled motor respectively
Go out module, non-electrical power input detection module communication connection.
The data processing chip connects with the controlled motor output module, power input detection module communication respectively
Connect, and be connected with gain control module communication is compared.The vehicle wheel rotational speed detection module is connected with by control electric vehicle module,
It is connected with gain control module communication is compared.It is described compare gain control module respectively with the data processing chip, the car
The communication connection of wheel speed detection module, and be connected with controlled motor output module communication.
Embodiment 5
The emulation experiment that embodiment 5~7 is related to, based on embodiment 1~4.
Load-carrying self adaptation
Simulating scenes：Vehicle is travelled in flat road surface, and load-carrying is respectively 90kg and 120kg.
Be can be seen that by Fig. 6 and Fig. 7：In the case of uncontrolled, vehicle can not be rapidly reached estimated speed, Ji Huwen
Relatively low velocity amplitude is scheduled on, and load-carrying is bigger, the velocity amplitude is smaller；In the case of controlled, vehicle can normally improve speed.
In the case of uncontrolled, driving moment is stable in a relatively low level after vehicle start, and in controlled feelings
Under condition, driving moment stabilization increases in a level higher with the increase of loading capacity.Therefore, the present invention have compared with
Good load-carrying adaptivity.
Embodiment 6
Gradient self adaptation
Simulating scenes：Vehicle does not increase load-carrying, and ramp, ramp angle (gradient) are entered after travelling 50m in flat road surface
Respectively 5% and 10%.
Be can be seen that by 8 and Fig. 9：In the case of uncontrolled, speed is decreased obviously, and the gradient is bigger, and speed declines
It is faster；And in the case of controlled, car speed is steady.In the case of uncontrolled, driving moment is steady after vehicle start
A relatively low level is scheduled on, and in the case of controlled, position short time of the driving moment from relatively low level
A higher level is inside brought up to, the level value determines that the gradient is bigger by the size of the gradient, and driving moment is bigger.Therefore, this hair
It is bright with preferable gradient adaptivity.
Embodiment 7
Load-carrying and gradient self adaptation under extreme condition
Simulating scenes：Load-carrying is 120kg, travels in the flat road surface and enter after 50m ramp, the gradient be respectively 15% and-
15%, that is, it is respectively and goes up a slope and descending.
Be can be seen that by 10 and Figure 11：During upward slope, in the case of uncontrolled, speed declines substantially, and is having control
In the case of, car speed slowly declines, and is finally maintaining a stable level；During descending, in the case of uncontrolled,
Speed rises rapidly, and in the case of controlled, the speed rate of climb is relatively slow.In the case of uncontrolled, driving force
Square is basically stable at a numerical value after vehicle start, in climb and fall all without changing；And in the case of controlled,
As can be seen that be immediately raised to a level higher when going up a slope, and stabilization is in this numerical value；Similarly, the car in descending
Drop to a relatively low level, and stabilization in a short time in this numerical value.The present invention reaches under extreme conditions
Load-carrying and gradient self adaptation.
Claims (10)
1. a kind of electric vehicle load-carrying and gradient self-adaptation control method, it is characterised in that：Comprise the following steps：
(1) dynamic torque, is measured：
Dynamic torque T*Including the first dynamic torque TrAnd/or the second dynamic torque Tp；
The first dynamic torque TrIt is vehicular electric machine moment of torsion, is exported by top level control device, the top level control device is stepped on for acceleration
One or more in plate, brake pedal, active safety control system；The first dynamic torque TrBy one or more motors
There is provided；Detected by torque sensor and obtained, or the current of electric that is measured by electric machine controller and other parameters are calculated and tried to achieve；
The second dynamic torque TpBy torque sensor detect manpower and/or engine to vehicle apply moment of torsion signal and
；
(2) preferable name wheel speed, is calculated：
The dynamic torque T measured by step (1)*It is calculated nominal wheel speed w ideally*；
The nominal wheel speed specific formula for calculation ideally is：
Jn=mr2+Jw
The meaning of each parameter is as follows in formula：T*：Dynamic torque, Jn：Ideally equivalent nominal rotary inertia, w*：It is preferable
Nominal wheel speed, m under state：The load-carrying that ideally wheel is shared, Jw：The rotary inertia of wheel, r：Radius of wheel；
(3) actual wheel speed, is measured：
Calculated by motor speed and directly export actual wheel speed w；
(4), compensation torque calculating：
By contrasting nominal wheel speed w*With actual wheel speed w, if w*It is close with w numerical value, then without calculating compensation moment of torsion；If w*
Differ larger with w, then calculate compensation torque Tmc；It is described to calculate compensation torque TmcAlgorithm be selected from pid control algorithm, fuzzy
One or more in control algolithm, optimal control algorithm, synovial membrane control algolithm；
(5) load-carrying and the gradient are adapted to：
According to the compensation torque T that step (4) is obtainedmc, the torque output of motor is adjusted, so as to realize load-carrying and the gradient of vehicle
Self adaptation.
2. a kind of electric vehicle load-carrying according to claim 1 and gradient self-adaptation control method, it is characterised in that：Step
(1) the second dynamic torque TpThe moment of torsion and/or engine applied to vehicle for driver apply moment of torsion to vehicle；Engine
Apply moment of torsion to vehicle to be obtained by throttle opening or distributive value.
3. a kind of electric vehicle load-carrying according to claim 1 and gradient self-adaptation control method, it is characterised in that：Step
(3) the actual wheel speed w is measured by external sensor.
4. a kind of electric vehicle load-carrying according to claim 1 and gradient self-adaptation control method, it is characterised in that：Step
(4) the compensation torque TmcComputing formula be：Tmc=K (w*-w)；Wherein, K represents gain coefficient.
5. a kind of electric vehicle load-carrying according to any one of Claims 1 to 4 and gradient self-adaptation control method, its feature
It is：Omit step (2)；In step (3), it is right that the formula for directly being provided using step (2) calculates actual wheel speed institute
The simulation dynamic torque T for answering；
In step (4), the dynamic torque T for directly being measured by simulation dynamic torque T and step (1)*Compare and calculate compensation moment of torsion
Tmc。
6. a kind of electric vehicle load-carrying according to any one of Claims 1 to 4 and gradient self-adaptation control method, its feature
It is：The wheel speed w and nominal wheel speed w*, respectively with wheel rotational accelerationWith name wheel rotational accelerationInstead of.
7. the vehicle of a kind of load-carrying of application electric vehicle and gradient self-adaptation control method, it is characterised in that：The vehicle is based on
A kind of electric vehicle load-carrying and gradient self-adaptation control method described in any one of claim 1~6；Including torque request mould
Block, non-electrical power input detection module, controlled motor output module, by control electric vehicle module, data processing chip, wheel
Rotating speed measring module, compare gain control module；
The torque request module is connected with top level control device, while being electrically connected with the controlled motor output module；It is described
Top level control device is one or more in accelerator pedal, brake pedal, active safety control system；First dynamic torque
As vehicular electric machine moment of torsion；
The non-electrical power input detection module is connected with the torque sensor of vehicle, is connected with engine control system communication,
It is connected with data processing chip communication, while being connected by control electric vehicle module communication with described；
The controlled motor output module is electrically connected with the torque request module, and gain control module Electricity Federation is compared with described
Connect；It is connected with data processing chip communication, and is connected with by control electric vehicle module communication；
The ECU control systems for passing through controlled electric vehicle by control electric vehicle module, control is travelled by control vehicle；Point
It is not connected with the controlled motor output module, non-electrical power input detection module communication；
The data processing chip is connected with the controlled motor output module, power input detection module communication respectively, and
It is connected with gain control module communication is compared；
The vehicle wheel rotational speed detection module is connected with by control electric vehicle module, is connected with gain control module communication is compared；
The gain control module that compares is connected with the data processing chip, vehicle wheel rotational speed detection module communication respectively,
And be connected with controlled motor output module communication.
8. the vehicle of application electric vehicle according to claim 7 load-carrying and gradient self-adaptation control method, its feature exists
In：The torque request module is used to receive top level control device feedack, the first power of generation top level control device output
Torque Tr；
The non-electrical power input detection module is used to detect that manpower and/or engine apply to turn round to vehicle by torque sensor
The signal of square, while obtaining the moment of torsion that engine applies to vehicle by throttle opening or distributive value, the second power of output is turned round
Square Tp；
The controlled motor output module is used to receive the first dynamic torque information T of torque request module generationrWith compare gain
The compensation torque information T of control module outputmc, and export the 3rd dynamic torque Tm；
It is described to be used to receive dynamic torque T by control electric vehicle module*, by being controlled the ECU control systems of electric vehicle, control
System is travelled by control vehicle；The dynamic torque T*The 3rd dynamic torque T including controlled motor output module outputmWith
Second dynamic torque T of non-electrical power input detection module outputp；
The data processing chip is by being calculated preferable name wheel speed w*；
The vehicle wheel rotational speed detection module is used to measure actual wheel rotating speed w；
The gain control module that compares compares w in real time*The difference of-w, and it is calculated compensation torque Tmc。
9. the vehicle of application electric vehicle according to claim 8 load-carrying and gradient self-adaptation control method, its feature exists
In：The vehicle wheel rotational speed detection module measures actual wheel rotating speed w by external sensor, or calculates direct by motor speed
Obtain.
10. application electric vehicle load-carrying according to claim 8 or claim 9 and the vehicle of gradient self-adaptation control method, it is special
Levy and be：Vehicle wheel rotational speed detection module is replaced with wheel acceleration detection module；Correspondingly, the wheel speed w and name are rotated
Fast w*, respectively with wheel rotational accelerationWith name wheel rotational accelerationInstead of.
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