CN111267628A - Suspension control method for magnetic-levitation train - Google Patents
Suspension control method for magnetic-levitation train Download PDFInfo
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- CN111267628A CN111267628A CN202010087902.9A CN202010087902A CN111267628A CN 111267628 A CN111267628 A CN 111267628A CN 202010087902 A CN202010087902 A CN 202010087902A CN 111267628 A CN111267628 A CN 111267628A
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
- B60L13/00—Electric propulsion for monorail vehicles, suspension vehicles or rack railways; Magnetic suspension or levitation for vehicles
- B60L13/04—Magnetic suspension or levitation for vehicles
- B60L13/06—Means to sense or control vehicle position or attitude with respect to railway
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
- B60L13/00—Electric propulsion for monorail vehicles, suspension vehicles or rack railways; Magnetic suspension or levitation for vehicles
- B60L13/04—Magnetic suspension or levitation for vehicles
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- Control Of Vehicles With Linear Motors And Vehicles That Are Magnetically Levitated (AREA)
- Vehicle Body Suspensions (AREA)
Abstract
The invention discloses a suspension control method of a magnetic-levitation train, and relates to the suspension control technology of the magnetic-levitation train. According to the control method, the optimal control parameters of the vehicle at different positions and/or under different working conditions are stored in the suspension controller, the suspension controller switches the control parameters to the optimal control parameters corresponding to the positions and/or the working conditions according to the real-time positions and the working conditions of the vehicle, so that the vehicle is subjected to suspension control by adopting different control parameters under different positions and/or working conditions, the optimal control under each position and/or working condition is realized, the problem that the suspension control is unstable due to the fact that only one group of control parameters exist in the whole operation line is solved, and the stability, reliability and comfort of vehicle control are improved.
Description
Technical Field
The invention belongs to the technical field of maglev train suspension control, and particularly relates to a maglev train suspension control method.
Background
The magnetic-levitation train utilizes electromagnetic force to support and guide the train body and the track, and the common magnetic-levitation trains at present comprise an electromagnetic levitation type magnetic-levitation train and an electric levitation type magnetic-levitation train. The electromagnetic suspension type magnetic suspension train uses the vehicle-mounted suspension electromagnet to generate a magnetic field, and generates a suction force with a track, so that a train body is suspended above the track. The gap between the suspension electromagnet and the track is generally 8-12mm, and the current of the suspension electromagnet is adjusted through the suspension controller to ensure that the train is stably suspended.
The suspension controller is one of the core components of the magnetic-levitation train, the function and performance of the suspension controller directly influence the stability, reliability and comfort of the magnetic-levitation train, and the suspension controller is an important guarantee for the safe operation of the magnetic-levitation train. Therefore, it is important to optimize and improve the levitation control method to improve the performance of the entire levitation system and the vehicle.
In order to ensure that the maglev train can suspend and run normally and stably, the requirement of the vehicle on the track and the line is higher, and the maglev train has the main advantages that: low noise, small turning radius, strong climbing capability and the like. Smaller turning radius can cause the track camber to be larger, the vehicle lateral acting force is big, and the lateral displacement that the electro-magnet produced is big, influences the electromagnetic force that produces between suspension electro-magnet and the track to influence suspension performance. The large ramp can generate a large vertical curve, and considering that the vehicle body is a rigid structure, when the vehicle passes through the large vertical curve, the vertical acting force can be greatly changed, which also brings challenges to the suspension controller and the control method. The suspension stability is also influenced by factors such as track construction and geological settlement, certain errors exist in the track precision of different positions of the same line, and track steps exist at the joint of the track and the track. Meanwhile, when the train runs on a line and the platform floats statically, the states of the train are different.
As shown in fig. 1, when the vehicle realizes static levitation by the control parameter set 1, the levitation gap is relatively smooth without obvious fluctuation and vibration. When the vehicle realizes static levitation by the control parameter group 2, the levitation gap fluctuation is large, and the vehicle vibration is obvious. It can be seen that the control parameter set 1 is more suitable for vehicle floating; however, when the vehicle is running, the control parameter set 2 has a better dynamic response effect, and the control parameter set 1 is no longer applicable. Therefore, the same set of control parameters is difficult to adapt to different position states and different working conditions of the whole operating line, and the requirements on the control method and the control parameters of the suspension controller are high. The method adopted by the existing suspension control is to select a group of control parameters which can adapt to the whole running line in a compromise way through continuous debugging and parameter optimization, so that the reliability and the comfort of the vehicle are greatly influenced and reduced.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides a suspension control method of a maglev train, which adopts different control parameters to realize suspension control of the vehicle when the vehicle is in different position states and different working conditions, so as to improve the reliability of the vehicle and a suspension controller and solve the problem that the same set of control parameters cannot adapt to the whole running line.
The invention solves the technical problems through the following technical scheme: a suspension control method of a magnetic-levitation train comprises the following steps:
step 1: acquiring optimal control parameters of a vehicle at different positions and/or under different working conditions, and storing the corresponding optimal control parameters at different positions and/or under different working conditions in a suspension controller;
step 2: acquiring real-time position information, real-time speed information and real-time uplink and downlink information of a vehicle;
and step 3: and 2, determining the current position and/or working condition of the vehicle according to the real-time position, the real-time speed and the real-time uplink and downlink information of the vehicle in the step 2, and switching the control parameters to the optimal control parameters corresponding to the position and/or working condition according to the current position and/or working condition of the vehicle so as to realize the suspension control of the vehicle at the position and/or working condition.
The suspension control method of the invention obtains the optimal control parameters corresponding to different positions and/or working conditions when the vehicle is at the different positions and/or the different working conditions, and the position and/or the working condition and the optimal control parameter corresponding to the position and/or the working condition are saved in the suspension controller, the suspension controller determines the current position and/or the working condition of the vehicle after acquiring the real-time position, the real-time speed and the real-time uplink and downlink information of the vehicle, and the control parameters are switched to the optimal control parameters corresponding to the current position and/or working condition, so that the suspension control is realized by adopting different control parameters under different positions and/or working conditions, the problem of unstable suspension control caused by only one group of control parameters of the whole running line is solved, and the stability, reliability and comfort of vehicle control are improved.
Further, the vehicle is located at a position including a platform, a curve, a ramp and a straight road; the working conditions of the vehicle comprise static suspension and dynamic suspension.
Further, the optimal control parameters include a nominal clearance, a balance point current, a desired current, and PID control parameters.
Further, in step 1, the optimal control parameters of the vehicle at different positions and/or under different working conditions are obtained through actual engineering debugging.
Further, the judgment basis for obtaining the optimal control parameters under different working conditions through actual engineering debugging is as follows:
for static suspension, the rated clearance is less than or equal to minus 0.5mm and less than or equal to plus 0.5mm, and the vehicle and the track have no resonance phenomenon;
for dynamic suspension, the rated clearance is smaller than or equal to-4 mm and the suspension clearance is smaller than or equal to +4mm, the vehicle and the track have no resonance phenomenon, and the vehicle has no phenomena of point dropping and track smashing when dynamically operating at different positions.
Further, in the step 2, the levitation controller acquires real-time position information, real-time speed information, and real-time uplink and downlink information of the vehicle through the CAN bus.
Further, in step 3, the current position information of the vehicle is determined based on the position information acquired through the CAN bus, and the accuracy of the current position is determined according to the real-time speed and the detection period, where the specific determination method is as follows:
if | SL-SiIf the | is less than or equal to the delta L, the current position information of the vehicle is accurate, and the control parameters are switched;
if | SL-SiIf the value is greater than delta L, sending an abnormal report of the vehicle position information without switching control parameters;
wherein S isLFor real-time position, S, obtained via the CAN busi＝Si-1+vi·T，SiFor the ith detection cycle the position of the vehicle, Si-1For the i-1 th detection cycle, the position of the vehicle, viThe real-time speed of the vehicle is detected in the ith detection period, T is the detection period, and Delta L is a set threshold value.
Further, the threshold Δ L is set to 10 m.
Further, in step 3, when the optimal control parameter is switched, the current optimal control parameter is gradually accumulated or reduced to the target optimal control parameter at a certain accumulation rate or reduction rate, and a specific switching mathematical expression is as follows:
Kij＝Kmn±q·k
wherein, KijFor the target optimum control parameter, KmnFor the current optimal control parameter, k is the accumulation rate or the accumulation deceleration rate, and q is the accumulation times or the accumulation deceleration times.
Further, the accumulation rate or accumulation deceleration rate k is 0.1.
Advantageous effects
Compared with the prior art, the suspension control method of the maglev train provided by the invention has the advantages that the optimal control parameters of the vehicle at different positions and/or under different working conditions are stored in the suspension controller, the suspension controller switches the control parameters to the optimal control parameters corresponding to the positions and/or the working conditions according to the real-time positions and the working conditions of the vehicle, so that the vehicle is subjected to suspension control by adopting different control parameters under different positions and/or working conditions, the optimal control under each position and/or working condition is realized, the problem of unstable suspension control caused by only one group of control parameters of the whole running line is avoided, and the stability, the reliability and the comfort of vehicle control are improved. When the control parameters are switched, in order to ensure the smooth transition of the control parameters, the current control parameters are not directly switched to the target control parameters, but the transition switching is carried out at a certain speed, so that the large fluctuation of vehicle control is avoided, and the stability, reliability and comfort of the vehicle control are further improved.
Drawings
In order to more clearly illustrate the technical solution of the present invention, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are only one embodiment of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on the drawings without creative efforts.
FIG. 1 is a comparison graph of the effects of different control parameters under different working conditions in the background art of the present invention;
FIG. 2 is a control flow chart of a levitation control method of a magnetic-levitation train according to an embodiment of the present invention;
FIG. 3 is a schematic illustration of vehicle position information in an embodiment of the present invention;
fig. 4 is a network topology diagram of the levitation controller in the embodiment of the present invention.
Detailed Description
The technical solutions in the present invention are clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
As shown in fig. 2, the levitation control method for a magnetic-levitation train provided by the present invention comprises:
1. and acquiring optimal control parameters of the vehicle at different positions or under different working conditions, and storing the corresponding optimal control parameters at different positions or under different working conditions in the suspension controller.
As shown in fig. 3, the whole track has different positions such as a platform, a curve, a ramp, a straight road, etc., and the vehicle has different working conditions when running at the different positions, such as static suspension and dynamic suspension at the platform, and dynamic suspension at the curve, the ramp and the straight road. In the existing suspension control of a vehicle, the whole operation line only has one group of control parameters, but the optimal control under different positions or working conditions cannot be realized through one group of control parameters, as shown in fig. 1. Therefore, the optimal control parameters of the vehicle at different positions or under different working conditions are obtained through actual engineering debugging, and when the vehicle is at the corresponding position or working condition, the suspension controller switches the control parameters to the optimal control parameters corresponding to the position or working condition, so that the optimal control of the vehicle is realized.
The judgment basis of the optimal control parameters of the vehicles under different working conditions is as follows:
for static suspension, the rated clearance is less than or equal to minus 0.5mm and less than or equal to plus 0.5mm, and the vehicle and the track have no obvious resonance phenomenon; for dynamic suspension, the rated clearance is smaller than or equal to-4 mm and the suspension clearance is smaller than or equal to +4mm, the vehicle and the track have no obvious resonance phenomenon, and the vehicle has no obvious phenomena of point dropping and track smashing when dynamically operating at different positions. In this embodiment, the nominal clearance is 8.5 mm.
For different positions, the optimal control parameters of the vehicle are determined through frequency response characteristics, at each position, due to the influences of factors such as track length, foundation settlement and the like, the tracks at the positions such as a platform, a curve, a ramp, a straight road and the like respectively show different frequency response characteristics, the frequency response characteristics of the corresponding position are optimal through adjusting each control parameter, and the control parameter at the moment is the optimal control parameter corresponding to the position.
The optimal control parameters obtained through actual engineering debugging at different positions or under different working conditions are stored in the suspension controller in a two-dimensional table form, as shown in table 1 below.
TABLE 1 optimal control parameters at different positions/conditions
When the vehicle runs to the station, the suspension controller switches the control parameter to K11、K12、K13、……、K1nWhen the vehicle runs to a curve, the suspension controller switches the control parameter to K21、K22、K23、……、K2nAnd so on.
The main control algorithm of the levitation controller is as follows:
i*＝i0+kp(s-s0)+ki∫(s-s0)+kds'，
where s is the actual gap of the electromagnet, i0To balance the point current, s0For nominal gap, s' is the velocity signal, which can be derived from the actual gap signal differentiation or the acceleration signal integration, kp、ki、kdFor PID control parameters, by continuously comparing s and s0Computing to obtain the expected current i*。
It follows that in the present invention, the optimal control parameter is the PID control parameter (k)p、ki、kd) Rated clearance s0Balance point current i0Desired current i*And other parameters needed in the control algorithm.
2. And acquiring real-time position information, real-time speed information and real-time uplink and downlink information of the vehicle.
As shown in fig. 4, the levitation controller acquires real-time position information, real-time speed information, and real-time uplink and downlink information of the vehicle through the CAN bus.
3. And 2, determining the current position or working condition of the vehicle according to the real-time position, the real-time speed and the real-time uplink and downlink information of the vehicle in the step 2, and switching the control parameter to the optimal control parameter corresponding to the position or the working condition according to the current position or the working condition of the vehicle so as to realize the suspension control of the vehicle at the position or under the working condition.
In order to further improve the suspension control precision, before the control parameter is switched, whether the current position of the vehicle is accurate or not is judged. The current position information of the vehicle is based on the position information acquired through a CAN bus, and the accuracy of the current position is judged according to the real-time speed and the detection period, wherein the specific judgment method comprises the following steps:
if | SL-SiIf the | is less than or equal to the delta L, the current position information of the vehicle is accurate, and the control parameters are switched;
if | SL-SiIf the value is greater than delta L, sending an abnormal report of the vehicle position information without switching control parameters;
wherein S isLFor real-time position, S, obtained via the CAN busi＝Si-1+vi·T，SiFor the ith detection cycle the position of the vehicle, Si-1For the i-1 th detection cycle, the position of the vehicle, viThe real-time speed of the vehicle (namely, the real-time speed obtained through the CAN bus) in the ith detection period is T, and the Delta L is a set threshold value. In this embodiment, the detection period T is 100us, and the threshold Δ L is set to 10m (meters). When the vehicle is running to the terminal, the vehicle position SiAnd Si-1And clearing all the points, and when the vehicle is restarted, accumulating and calculating the position of the vehicle again to obtain the current position of the vehicle.
When a vehicle enters from one position to another position or enters from one working condition to another working condition, the control parameters need to be switched, the suspension controller switches the control parameters, the suspension controller does not directly switch from one group of control parameters to another group of control parameters, but gradually accumulates or gradually reduces the current optimal control parameters to the target optimal control parameters at a certain accumulation rate or an accumulation reduction rate, the switching of the control parameters is realized, the smooth transition of the control parameters is ensured, the large fluctuation of vehicle control is avoided, and the stability, reliability and comfort of vehicle control are further improved.
The switching formula of the control parameters is as follows:
Kij＝Kmn±q·k
wherein, KijOptimizing control parameters for a target，KmnFor the current optimal control parameter, k is the accumulation rate or the accumulation deceleration rate, and q is the accumulation times or the accumulation deceleration times. In this embodiment, the accumulation rate or the accumulation deceleration rate k is 0.1. The accumulation rate or the accumulation deceleration rate can also be understood as an accumulation step length or an accumulation deceleration step length, and the selection of k is related to the target optimal control parameter, the current optimal control parameter and the accumulation times or the accumulation deceleration times, and can also be adjusted according to actual needs, mainly to ensure the smooth switching of the control parameters.
The above disclosure is only for the specific embodiments of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art can easily conceive of changes or modifications within the technical scope of the present invention, and shall be covered by the scope of the present invention.
Claims (10)
1. A suspension control method of a magnetic-levitation train is characterized by comprising the following steps:
step 1: acquiring optimal control parameters of a vehicle at different positions and/or under different working conditions, and storing the corresponding optimal control parameters at different positions and/or under different working conditions in a suspension controller;
step 2: acquiring real-time position information, real-time speed information and real-time uplink and downlink information of a vehicle;
and step 3: and 2, determining the current position and/or working condition of the vehicle according to the real-time position, the real-time speed and the real-time uplink and downlink information of the vehicle in the step 2, and switching the control parameters to the optimal control parameters corresponding to the position and/or working condition according to the current position and/or working condition of the vehicle so as to realize the suspension control of the vehicle at the position and/or working condition.
2. The levitation control method of claim 1, wherein the vehicle is located at a position selected from the group consisting of a platform, a curve, a ramp, and a straight track; the working conditions of the vehicle comprise static suspension and dynamic suspension.
3. The levitation control method of claim 1, wherein the optimal control parameters comprise a nominal gap, a balance point current, a desired current, and PID control parameters.
4. A suspension control method for a magnetic-levitation train as recited in any one of claims 1-3, wherein in step 1, the optimal control parameters of the vehicle at different positions and/or under different working conditions are obtained by actual engineering debugging.
5. The levitation control method of the magnetic-levitation train as recited in claim 4, wherein the judgment basis for obtaining the optimal control parameters under different working conditions through actual engineering debugging is as follows:
for static suspension, the rated clearance is less than or equal to minus 0.5mm and less than or equal to plus 0.5mm, and the vehicle and the track have no resonance phenomenon;
for dynamic suspension, the rated clearance is smaller than or equal to-4 mm and the suspension clearance is smaller than or equal to +4mm, the vehicle and the track have no resonance phenomenon, and the vehicle has no phenomena of point dropping and track smashing when dynamically operating at different positions.
6. The levitation control method of claim 1, 2, 3 or 5, wherein in step 2, the levitation controller obtains real-time position information, real-time speed information and real-time uplink and downlink information of the vehicle through the CAN bus.
7. The levitation control method of claim 1, 2, 3 or 5, wherein in the step 3, the current position information of the vehicle is based on the position information obtained through the CAN bus, and the accuracy of the current position is determined according to the real-time speed and the detection period, and the specific determination method is as follows:
if | SL-SiIf the | is less than or equal to the delta L, the current position information of the vehicle is accurate, and the control parameters are switched;
if | SL-SiIf the value is greater than delta L, sending an abnormal report of the vehicle position information without switching control parameters;
wherein S isLFor real-time position, S, obtained via the CAN busi＝Si-1+vi·T，SiFor the ith detection cycle the position of the vehicle, Si-1For the i-1 th detection cycle, the position of the vehicle, viThe real-time speed of the vehicle is detected in the ith detection period, T is the detection period, and Delta L is a set threshold value.
8. The levitation control method of claim 7, wherein the threshold Δ L is set to 10 m.
9. The levitation control method for a magnetic-levitation train as recited in claim 1, 2, 3 or 5, wherein in the step 3, when the optimal control parameter is switched, the current optimal control parameter is gradually accumulated or reduced to the target optimal control parameter at a certain accumulation rate or a certain reduction rate, and the specific switching mathematical expression is as follows:
Kij＝Kmn±q·k
wherein, KijFor the target optimum control parameter, KmnFor the current optimal control parameter, k is the accumulation rate or the accumulation deceleration rate, and q is the accumulation times or the accumulation deceleration times.
10. A method for controlling levitation of a magnetic levitation train as recited in claim 9, wherein said cumulative velocity or cumulative deceleration k is 0.1.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN113561786A (en) * | 2021-08-26 | 2021-10-29 | 同济大学 | Suspension redundancy control system and method based on rail state monitoring |
| WO2024087289A1 (en) * | 2022-10-27 | 2024-05-02 | 中车株洲电力机车有限公司 | Maglev train control method and related apparatus |
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| CN108897211A (en) * | 2018-07-19 | 2018-11-27 | 中国人民解放军国防科技大学 | Parameter optimization method for suspension control system of magnetic-levitation train |
| CN108919782A (en) * | 2018-07-12 | 2018-11-30 | 中铁磁浮科技（成都）有限公司 | A kind of method that suspension control parameter adapts to line adjustment |
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| CN108919782A (en) * | 2018-07-12 | 2018-11-30 | 中铁磁浮科技（成都）有限公司 | A kind of method that suspension control parameter adapts to line adjustment |
| CN108897211A (en) * | 2018-07-19 | 2018-11-27 | 中国人民解放军国防科技大学 | Parameter optimization method for suspension control system of magnetic-levitation train |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN113561786A (en) * | 2021-08-26 | 2021-10-29 | 同济大学 | Suspension redundancy control system and method based on rail state monitoring |
| CN113561786B (en) * | 2021-08-26 | 2024-01-12 | 同济大学 | Suspension redundancy control system and method based on vehicle rail state monitoring |
| WO2024087289A1 (en) * | 2022-10-27 | 2024-05-02 | 中车株洲电力机车有限公司 | Maglev train control method and related apparatus |
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