CN109484384A - A kind of optimal adhesion braking control method of bullet train and system - Google Patents
A kind of optimal adhesion braking control method of bullet train and system Download PDFInfo
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- CN109484384A CN109484384A CN201811120255.6A CN201811120255A CN109484384A CN 109484384 A CN109484384 A CN 109484384A CN 201811120255 A CN201811120255 A CN 201811120255A CN 109484384 A CN109484384 A CN 109484384A
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60T—VEHICLE BRAKE CONTROL SYSTEMS OR PARTS THEREOF; BRAKE CONTROL SYSTEMS OR PARTS THEREOF, IN GENERAL; ARRANGEMENT OF BRAKING ELEMENTS ON VEHICLES IN GENERAL; PORTABLE DEVICES FOR PREVENTING UNWANTED MOVEMENT OF VEHICLES; VEHICLE MODIFICATIONS TO FACILITATE COOLING OF BRAKES
- B60T8/00—Arrangements for adjusting wheel-braking force to meet varying vehicular or ground-surface conditions, e.g. limiting or varying distribution of braking force
- B60T8/17—Using electrical or electronic regulation means to control braking
- B60T8/1701—Braking or traction control means specially adapted for particular types of vehicles
- B60T8/1705—Braking or traction control means specially adapted for particular types of vehicles for rail vehicles
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60T—VEHICLE BRAKE CONTROL SYSTEMS OR PARTS THEREOF; BRAKE CONTROL SYSTEMS OR PARTS THEREOF, IN GENERAL; ARRANGEMENT OF BRAKING ELEMENTS ON VEHICLES IN GENERAL; PORTABLE DEVICES FOR PREVENTING UNWANTED MOVEMENT OF VEHICLES; VEHICLE MODIFICATIONS TO FACILITATE COOLING OF BRAKES
- B60T8/00—Arrangements for adjusting wheel-braking force to meet varying vehicular or ground-surface conditions, e.g. limiting or varying distribution of braking force
- B60T8/17—Using electrical or electronic regulation means to control braking
- B60T8/171—Detecting parameters used in the regulation; Measuring values used in the regulation
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60T—VEHICLE BRAKE CONTROL SYSTEMS OR PARTS THEREOF; BRAKE CONTROL SYSTEMS OR PARTS THEREOF, IN GENERAL; ARRANGEMENT OF BRAKING ELEMENTS ON VEHICLES IN GENERAL; PORTABLE DEVICES FOR PREVENTING UNWANTED MOVEMENT OF VEHICLES; VEHICLE MODIFICATIONS TO FACILITATE COOLING OF BRAKES
- B60T8/00—Arrangements for adjusting wheel-braking force to meet varying vehicular or ground-surface conditions, e.g. limiting or varying distribution of braking force
- B60T8/32—Arrangements for adjusting wheel-braking force to meet varying vehicular or ground-surface conditions, e.g. limiting or varying distribution of braking force responsive to a speed condition, e.g. acceleration or deceleration
- B60T8/58—Arrangements for adjusting wheel-braking force to meet varying vehicular or ground-surface conditions, e.g. limiting or varying distribution of braking force responsive to a speed condition, e.g. acceleration or deceleration responsive to speed and another condition or to plural speed conditions
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- Engineering & Computer Science (AREA)
- Transportation (AREA)
- Mechanical Engineering (AREA)
- Regulating Braking Force (AREA)
- Train Traffic Observation, Control, And Security (AREA)
- Electric Propulsion And Braking For Vehicles (AREA)
Abstract
The invention proposes a kind of optimal adhesion braking control method of bullet train and systems, realize the estimation of real-time creep rate and the compensation of unknown quantity while the effective performance for also ensuring that brake force.The present invention can realize the estimation and tracking to the optimal creep rate of different rail levels under rail level environment complicated and changeable, the brake force of bullet train can effectively be played, to can further improve the stability of braking system.
Description
Technical field
The present invention relates to locomotive brake control technology fields, more particularly, to a kind of optimal adhesion braking of bullet train
Control method and system.
Background technique
Bullet train has become the direction and goal of China railways future development.With the continuous speed-raising of train, railway fortune
Defeated safe performance indexes also increasingly improve.Safety is to measure the most important standard of shipping mass, therefore braking system is necessary
With very high reliability.
When implementing braking, the performance of brake force depends on wheel and is formed in contact process between rail train
Adhesion strength.Since adhesion coefficient is limited between by wheel track, the brake force applied cannot be excessive.Between wheel track if more than
Adhesion limitation, will slide between wheel and rail surface, lead to wheel track severe friction, cause the improper mill of wheel tread
Consumption, seriously affects train operating safety.Experiment also indicates that the creep state between the size and wheel track of adhesion strength has interwoveness
Connection.However the adhesion between wheel track is in the non-linear of high intensity, it is difficult to accurate to obtain.The presence of problem above seriously affects
Effective performance of braking force of train.
The research of current adhesion braking control method is concentrated mainly on two aspects: best creep rate or creep speed
Obtain the design with controller.Control method is mostly control target with creep rate or creep speed, to make train operation most
Near good sticky point, optimal adhesion braking control is realized.However during train operation, when the creep rate of different rail levels is
Become unknown, it is difficult to accurate to obtain.Therefore the optimal creep rate for how finding time-varying rail level, is the key that a needs solve to ask
Topic.On the other hand, for the design of controller, unknown quantity present in braking system and disturbance are not considered excessively at present,
This certainly will will affect the accuracy of control.
Summary of the invention
The technical problem to be solved by the present invention is to it is optimal viscous to provide a kind of bullet train for prior art deficiency and defect
Brake control method and system.Purpose is to realize the benefit of real-time estimation and system unknowns to the optimal creep rate of different rail levels
It repays, it is ensured that the tracking to optimal creep rate, to guarantee effective performance of brake force.
To achieve the above object, the invention adopts the following technical scheme: a kind of optimal adhesion braking controlling party of bullet train
Method, comprising the following steps:
Step S1: kinetic model during high-speed train braking is established:Wherein ω
To take turns angular velocity, v is train speed, λ is creep rate, M is axis weight, J is rotary inertia, BtFor Uncertainty viscous friction system
Number, F are adhesion strength, r is wheel pair radius, FKTo take turns the total brake force provided to all brake linings, rzFor the average friction half of brake disc
Diameter, TDFor Uncertainty perturbed force；According to state equation during kinetic model acquisition high-speed train braking:Wherein braking moment U=FKrz, total Uncertainty fD=(TD-Btω), state variable x1=v, x2=
ωr；
Step S2: adhesiveness discretization equation Y (k)=U between wheel track is establishedT(k) θ (k), wherein Y (k)=μ0λ(k)-μ
(k), UT(k)=[μ (k) λ (k), μ (k) λ2(k)], θT(k)=[P1(k),P2(k)], μ0For adhesiveness curve initial slope,
P in parameter matrix θ (k)1、P2For rail level parameter；It solves parameter matrix θ (k) in above-mentioned equation and obtains optimal creep rate as reference
Creep rate λp；
Step S3: sliding mode observer is designed for estimating f according to state equation described in step S1DAnd F；
Step S4: design creep rate tracker is used for track reference creep rate, the ginseng that tracker applying step S2 is obtained
Examine creep rate λp, f in step S3DAnd F, to realize control target, so that the best braking ability of bullet train.
Further, parameter matrix θ (k) is solved in step S2 using the recurrence least square for having time-variant delays
Method, recursion equation are as follows:
K (k+1) in the recursion equation, P (k+1) are
Intermediate variable matrix, ρ are forgetting factorWherein α > 0,0 < ρ < 1；Thus it obtains with reference to creep rate
Further, the sliding mode observer in step S3, embodies are as follows:With Respectively x1,x2Observation, k1,k2,L1,L2It is the constant to be designed greater than zero；Pass through
Sliding mode observer is observed obtaining:So as to:Wherein
Further, the creep rate tracker in step S4, embodies are as follows:Wherein e is practical creep rate λ and refers to creep rate λpError e
=λ-λp, s is non-singular terminal sliding-mode surfaceβ is normal number, and p and q are positive odd number and satisfaction
A kind of optimal adhesion braking control system of bullet train, including operation result of measurement module and adhesion braking control module；
Operation result of measurement module is specially to take turns to be separately connected the first sliding mode observer and first arithmetic device, car body to velocity sensor output end
Velocity sensor output end is separately connected the second sliding mode observer and first arithmetic device, and first arithmetic device output end Connecting quantity is estimated
Gauge, parameter estimator output end connect second arithmetic device, the first sliding mode observer, the second sliding mode observer and second arithmetic device
Output end be connected to third arithmetic unit；
Wheel is known wheel pair radius, the bullet train speed of service to speed omega r, r for obtaining wheel to velocity sensor
Sensor is for obtaining train running speed v；
First arithmetic device is for obtaining current creep rateWherein x1=v, x2=ω r；
Parameter estimator uses the recurrent least square method with time-variant delays to estimate rail level state parameter P1、P2；The
Two arithmetic units refer to creep rate for calculatingFirst sliding mode observer, the second sliding mode observer are respectively used to obtain viscous
Put forth effort observationNonlinear termsSo as to obtain total interference volume observationThird arithmetic unit is used for track reference creep rate λpOutput optimum braking force square is simultaneously sent to
Adhesion braking control module is implemented to brake to train, and the arithmetic unit expression formula isWherein e is practical creep rate λ and refers to creep rate λpError e
=λ-λp, s is non-singular terminal sliding-mode surfaceβ is normal number, and p and q are positive odd number and satisfaction
Further, the recursion equation that the parameter estimator uses specifically:Y (k)=U in the recursion equationT(k) θ (k), wherein Y (k)
=μ0λ (k)-μ (k), UT(k)=[μ (k) λ (k), μ (k) λ2(k)], θT(k)=[P1(k),P2(k)], μ0For adhesiveness curve
Initial slope, K (k+1), P (k+1) are intermediate variable matrix, and ρ is forgetting factorWherein α > 0,0 < ρ < 1.
Further, the first sliding mode observer expression formula isSecond sliding mode observer expression formula is
Further the adhesion braking control module be system execution module, including DSP train brake control unit and
Brake rigging, the DSP train brake control unit receive the braking moment that third arithmetic unit is sent and are converted into brake finger
Order is sent to brake rigging, and the brake rigging is sequentially connected electricity empty switching valve, relay valve, checking cylinder, system
Moving plate.
The invention has the benefit that optimal adhesion braking control method proposed by the present invention and system, are realized compacted in real time
The estimation of sliding rate and the compensation of unknown quantity while the effective performance for also ensuring that brake force.The present invention can be in rail level ring complicated and changeable
Realize estimation and tracking to the optimal creep rate of different rail levels under border, can effectively play the brake force of bullet train, so as into
The stability of one step raising braking system.
Detailed description of the invention
Fig. 1 is the flow chart of one embodiment provided by the invention.
Fig. 2 is the structural schematic diagram of one embodiment provided by the invention.
Fig. 3 is adhesiveness curve synoptic diagram in one provided by the invention implementation.
Fig. 4 is to estimate different rail level parameter P in one provided by the invention implementation1Emulation schematic diagram.
Fig. 5 is to estimate different rail level parameter P in one provided by the invention implementation2Emulation schematic diagram.
Fig. 6 is the emulation schematic diagram that unknown quantity F is observed in one provided by the invention implementation.
Fig. 7 is to observe unknown quantity F in one provided by the invention implementationMEmulation schematic diagram.
Fig. 8 is that train running speed emulates schematic diagram in one provided by the invention implementation.
Fig. 9 is that train operation creep rate emulates schematic diagram in one provided by the invention implementation.
Figure 10 is that train operation adhesion coefficient emulates schematic diagram in one provided by the invention implementation.
Specific embodiment
The present invention is further illustrated With reference to embodiment.
Embodiment 1 --- the optimal adhesion braking control method of bullet train:
According to the force analysis of train braking, kinetic model expression is established to train braking process first are as follows:
B in formula (1)tFor unknown viscous friction coefficient, TDBe adhesion strength for unknown perturbed force, F, r be wheel pair radius,
FKTo take turns the total brake force provided to all brake linings, rzMean friction radius, ω for brake disc are that wheel angular velocity, J rotation are used
Amount.
Wherein, adhesion strength expression formula are as follows:
F=μ (λ) Mg (2)
M is axis weight in formula (2), and v is train speed, and g is acceleration of gravity, and λ is creep rate, and μ (λ) is using λ as variable
Adhesion coefficient；Wherein, creep rate
Train rail level in actual motion is time-varying, according to the rail level characteristic real-time update of train actual motion with reference to compacted
Sliding rate λ, by mechanism of adhering between wheel track it is found that there is non-linear relation between adhesion coefficient and creep rate, the present embodiment is used
Wheel track between adhesiveness mathematical model expression formula are as follows:
μ in formula (3)0For adhesiveness curve initial slope, λ is creep rate, and μ (λ) is the adhesion coefficient using λ as variable,
P1、P2For rail level parameter.
The adhesiveness curve being illustrated in figure 3 under different rail levels, for different rail levels, adhesion coefficient is all with creep rate
Increase first increase and reduce afterwards, and there are optimal creep rates to correspond to unique peak point.The peak point left side is adhesioin zone, and the right is
Sliding area.The target of adhesion control is that the creep rate of train is allowed to remain near optimum value, it is made to operate in maximum adhesion
Coefficient region, to obtain optimal brake force.The creep rate at adhesion coefficient peak point is present in single order inverse as shown in Figure 3
At zero, then to adhesiveness model expression formula (3) the right and left derivation:
It can thus be concluded that creep rate and adhesion coefficient at peak point are as follows:
The optimal creep rate λ known to formula (5)mWith adhesion coefficient μm(λm) by P1、P2It determines.If P therefore can be estimated1、P2
Value, the optimal creep rate and adhesion coefficient of current rail level can be obtained, formula (3), which is made equivalent variations, to be obtained:
It enables: UT(k)=[μ (k) λ (k), μ (k) λ2(k)], Y (k)=μ0λ (k)-μ (k), θT(k)=[P1(k),P2(k)]；
Then adhesiveness mathematical model expression formula can be of equal value as follows between wheel track:
Y (k)=UT(k)θ(k) (7)
Parameter matrix θ (k) is estimated using the recurrent least square method with time-variant delays in the present embodiment, specifically
It is as follows:
K (k+1) in formula (8), P (k+1) are intermediate variable matrix, and ρ is 0 < ρ < 1 of forgetting factor.
When larger change occurs for rail level, creep rate can also change accordingly, then cannot according to fixed forgetting factor
The effectively variation of tracking rail level, therefore introduce the forgetting factor of time-varying are as follows:Wherein α > 0.
The meaning of the forgetting factor is: when rail level situation be in it is slowly varying when, the variation of creep rate can be smaller, phase
The forgetting factor value answered is with regard to bigger, then algorithm for estimating will remember the influence of most data in the past；And when rail level state is sent out
When raw mutation, the variation of creep rate is with regard to bigger, and corresponding forgetting factor value is with regard to smaller, then algorithm for estimating will be forgotten
The influence for going most data starts new data accumulating, to can ensure that the accuracy to different time-varying rail level parameter Estimations.
Existing definition status variable x1=v, x2=ω r, braking moment U=FKrz, the total unknown quantity of system is fD=(TD-Bt
ω), the state equation during its train braking is obtained according to train braking kinetic model are as follows:
Control strategy of adhering is that creep rate is indirectly controlled by the size of regulating brake force square, realizes the actual creep of train
Tracking of the rate to optimal creep rate.So that train is operated in always near adhesiveness peak of curve point, it is ensured that best braking
Energy.
It defines practical creep rate λ and refers to creep rate λpError e=λ-λp, then have:
It is of equal value as follows:
Define non-singular terminal sliding-mode surface are as follows:
β is normal number in formula (11), and p and q are positive odd number and satisfaction
Design creep rate tracking control unit are as follows:
In view of there are unknown quantity f in systemDAnd adhesion strength F is difficult to obtain, formula (12) controller is difficult to realize, and is now adopted
With sliding mode observer to unknown quantity fDIt is observed with F.Sliding mode observer is as follows:
Define the error between observation and actual value
Quote Lyapunov functionSo:
k1Meet the following conditions:And σ is any normal number, then
When system reaches sliding-mode surfaceThen
It enablesSimilarly, it quotes
Lyapunov functionk2Meet the following conditions k2≥|FM|+δ and δ are any normal number, reach sliding-mode surfaceI.e.
To sum up, unknown observation is obtained by sliding mode observer are as follows:It then can be with
It obtains:
By observationInstead of actual value fD, F brings into the design of controller, then can obtain optimum braking force by formula (12)
Square are as follows:
Embodiment 2 --- the optimal adhesion braking control system of bullet train:
As shown in Fig. 2, including operation result of measurement module and adhesion braking control module；Operation result of measurement module is specially to take turns to speed
Degree sensor output is separately connected the first sliding mode observer and first arithmetic device, and body speed of vehicle sensor output is separately connected
Second sliding mode observer and first arithmetic device, first arithmetic device output end Connecting quantity estimator, parameter estimator output end connect
Second arithmetic device is connect, the output end of the first sliding mode observer, the second sliding mode observer and second arithmetic device is connected to third operation
Device；For track reference creep rate λpOutput optimum braking force square is simultaneously sent to adhesion braking control module to train implementation system
It is dynamic.
It wherein takes turns to velocity sensor and body speed of vehicle sensor difference collection wheel to speed omega r, train running speed v；
First arithmetic device obtains current creep rate using the creep rate calculation formula in embodiment 1；Parameter estimator is using in embodiment 1
Rail level parameter matrix method for solving obtain rail level parameter；Second arithmetic device is obtained using the best creep rate formula in embodiment 1
It takes with reference to creep rate；Third arithmetic unit obtains optimum braking force square U using the creep rate tracker in embodiment 1 and is sent to adhesion
Brake module.
Adhesion braking control module is system execution module, including DSP train brake control unit and brake rigging,
The braking moment that the DSP train brake control unit receives the transmission of third arithmetic unit is converted into braking instruction and is sent to basic system
Dynamic device, the brake rigging are sequentially connected electricity empty switching valve, relay valve, checking cylinder, brake disc.
Numerical simulation is carried out to control method in the present embodiment and system below: considering train practical operation situation, high speed
Train starts to be braked with 55m/s (198km/h) initial velocity, and train operation is arranged in 3 kinds of different rail level conditions.Preceding
10s, train operation is in height adhesion rail level；10-20s is low adhesion rail level；20-30s is then extremely low adhesion rail level.Table 1 is high speed
Train simulation parameter；Table 2 is the simulation parameter of three kinds of different rail levels；When to simulate train actual motion there is interference in measurement data
Property, in estimation parameter P1P2When to be also added into mean value be the Gaussian noise that 0 variance is 0.1.
Fig. 4 is rail level parameter P1Actual value and estimated value, when in-orbit face environmental catastrophe, estimated value about in 10.06s and
20.12s converging to actual value.Rail level parameter P2Actual value and estimated value as shown in figure 5, being mutated for rail level, estimated value is big
About actual value is traced into 10.05s and 20.08s.Therefore algorithm for estimating can track the variation of rail level well, correctly estimate
Different rail level parameters.Fig. 6 and Fig. 7 is unknown quantity F, FMActual value and observation contrast simulation schematic diagram, for
Different rail levels, observation can preferably trace into given value, and only when rail level switches 10s and 20s, smaller tremble occurs in observation
It is dynamic.Known to observer to the observation of unknown quantity timeliness with higher and accuracy, therefore wanting for controller design can be met
It asks.
1 bullet train simulation parameter of table
The different rail level simulation parameters of table 2
When in-orbit face ring border is gradually deteriorated as shown in Figure 8, braking curve variation realizes train smooth system than more gentle
It is dynamic.Train known to Fig. 9 can be operated in substantially near the optimal creep rate of different rail levels.Figure 10 is arranged it is found that in braking process
Vehicle can be operated in substantially near the maximum sticky point of different rail levels, to guarantee that train has preferable brake force.To sum up, it emulates
As a result it is found that the present embodiment control method and system can effectively play the brake force of train, good braking effect is obtained.
Embodiment described above is only to absolutely prove preferred embodiment that is of the invention and being lifted, protection model of the invention
It encloses without being limited thereto.Those skilled in the art's made equivalent substitute or transformation on the basis of the present invention, in the present invention
Protection scope within.
Claims (8)
1. a kind of optimal adhesion braking control method of bullet train, which comprises the following steps:
Step S1: kinetic model during high-speed train braking is established:Wherein ω is wheel pair
Angular speed, v are train speed, λ is creep rate, M is axis weight, J is rotary inertia, BtIt is for uncertain viscous friction coefficient, F
Adhesion strength, r are wheel pair radius, FKTo take turns the total brake force provided to all brake linings, rzMean friction radius, T for brake discD
For uncertain disturbance；According to state equation during kinetic model acquisition high-speed train braking:Its
Middle braking moment U=FKrz, total unknown quantity fD=(TD-Btω), state variable x1=v, x2=ω r；
Step S2: adhesiveness discretization equation Y (k)=U between wheel track is establishedT(k) θ (k), wherein Y (k)=μ0λ (k)-μ (k),
UT(k)=[μ (k) λ (k), μ (k) λ2(k)], θT(k)=[P1(k),P2(k)], μ0For adhesiveness curve initial slope, parameter
P in matrix θ (k)1、P2For rail level parameter；It solves parameter matrix θ (k) in above-mentioned equation and obtains optimal creep rate as with reference to creep
Rate λp；
Step S3: sliding mode observer is designed for estimating f according to state equation described in step S1DAnd F；
Step S4: design creep rate tracker is used for track reference creep rate, and the creep rate tracker receiving step S2 is obtained
Reference creep rate λp, f in step S3DAnd F, to realize control target, so that the best braking ability of bullet train.
2. the optimal adhesion braking control method of a kind of bullet train according to claim 1, which is characterized in that in step S2
Parameter matrix θ (k) is solved using the recurrent least square method for having time-variant delays, recursion equation are as follows:K (k+1) in the recursion equation, P (k+1) are intermediate variable
Matrix, ρ are forgetting factorWherein α > 0,0 < ρ < 1；By the recurrence minimum two with time-variant delays
Multiplication is obtained with reference to creep rate
3. the optimal adhesion braking control method of a kind of bullet train according to claim 1, which is characterized in that in step S3
Sliding mode observer, embody are as follows:WithWhereinRespectively x1,x2Observation,k1,k2,L1,L2It is the constant to be designed greater than zero；It observes obtaining by sliding mode observer:
4. the optimal adhesion braking control method of a kind of bullet train according to claim 1, which is characterized in that in step S4
Creep rate tracker, embody are as follows:Wherein e is practical compacted
Sliding rate λ and reference creep rate λpError e=λ-λp, s is non-singular terminal sliding-mode surfaceβ is normal number, p and q
For positive odd number and satisfaction
5. a kind of optimal adhesion braking control system of bullet train, which is characterized in that including operation result of measurement module and adhesion braking
Control module；Operation result of measurement module is specially to take turns to be separately connected the first sliding mode observer and the first fortune to velocity sensor output end
Device is calculated, body speed of vehicle sensor output is separately connected the second sliding mode observer and first arithmetic device, first arithmetic device output end
Connecting quantity estimator, parameter estimator output end connect second arithmetic device, the first sliding mode observer, the second sliding mode observer and
The output end of second arithmetic device is connected to third arithmetic unit；
Wheel is known wheel pair radius, bullet train speed of service sensing to speed omega r, r for obtaining wheel to velocity sensor
Device is for obtaining train running speed v；
First arithmetic device is for obtaining current creep rateWherein x1=v, x2=ω r；
Parameter estimator uses the recurrent least square method with time-variant delays to estimate rail level state parameter P1、P2；Second fortune
It calculates device and refers to creep rate for calculatingFirst sliding mode observer, the second sliding mode observer are respectively used to obtain adhesion strength
ObservationTotal interference volume observationThird arithmetic unit is for tracking ginseng
Examine creep rate λpOutput optimum braking force square is simultaneously sent to adhesion braking control module to train implementation braking, the arithmetic unit table
It is up to formulaWherein e is practical creep rate λ and refers to creep rate λp's
Error e=λ-λp, s is non-singular terminal sliding-mode surfaceβ is normal number, and p and q are positive odd number and satisfaction
6. the optimal adhesion braking control system of a kind of bullet train according to claim 5, which is characterized in that the parameter
The recursion equation that estimator uses specifically:The recurrence side
Y (k)=U in journeyT(k) θ (k), wherein Y (k)=μ0λ (k)-μ (k), UT(k)=[μ (k) λ (k), μ (k) λ2(k)], θT(k)=
[P1(k),P2(k)], μ0For adhesiveness curve initial slope, K (k+1), P (k+1) are intermediate variable matrix, and ρ is forgetting factorWherein α > 0,0 < ρ < 1.
7. the optimal adhesion braking control system of a kind of bullet train according to claim 5, which is characterized in that the first sliding formwork
Observer expression formula isSecond sliding mode observer expression formula is
8. the optimal adhesion braking control system of a kind of bullet train according to claim 5, which is characterized in that the adhesion
Brake control module is system execution module, including DSP train brake control unit and brake rigging, the DSP train
The braking moment that brak control unit receives the transmission of third arithmetic unit is converted into braking instruction and is sent to brake rigging, described
Brake rigging is sequentially connected electricity empty switching valve, relay valve, checking cylinder, brake disc.
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Cited By (4)
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| CN110450794A (en) * | 2019-08-26 | 2019-11-15 | 西南交通大学 | A kind of optimized adhesion control method based on optimal creep speed search and tracking |
| WO2021022705A1 (en) * | 2019-08-07 | 2021-02-11 | 中车唐山机车车辆有限公司 | Anti-skid control method and apparatus for rail vehicle, and rail vehicle system |
| CN113997914A (en) * | 2020-07-28 | 2022-02-01 | 株洲中车时代电气股份有限公司 | Rail vehicle brake control method and device |
| CN117439446A (en) * | 2023-12-13 | 2024-01-23 | 西南交通大学 | Wheel rail slip control method based on wheel rail friction and wear testing machine |
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| CN103183037A (en) * | 2011-12-29 | 2013-07-03 | 中国北车股份有限公司大连电力牵引研发中心 | Electric locomotive adhesion control method and device |
| US20140277883A1 (en) * | 2013-03-15 | 2014-09-18 | General Electric Company | System and method of vehicle system control |
| CN105128872A (en) * | 2015-07-21 | 2015-12-09 | 株洲南车时代电气股份有限公司 | Adhesion control method of motor train unit |
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| CN110450794A (en) * | 2019-08-26 | 2019-11-15 | 西南交通大学 | A kind of optimized adhesion control method based on optimal creep speed search and tracking |
| CN113997914A (en) * | 2020-07-28 | 2022-02-01 | 株洲中车时代电气股份有限公司 | Rail vehicle brake control method and device |
| CN113997914B (en) * | 2020-07-28 | 2022-06-21 | 株洲中车时代电气股份有限公司 | Rail vehicle brake control method and device |
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