专利摘要:
The invention relates to a method for controlling a pressure medium supply for at least one hydraulic actuator (110), which is supplied with a pressure medium quantity by a variable-speed variable displacement pump in which a variable displacement drive (122) is driven by a variable speed drive (121) in a displacer volume per cycle. determined by a given pressure and / or volumetric flow profile, wherein a speed solving value (nson) and a setpoint (ason) for the displacement volume per cycle determining characteristic for a process flow are given by a model based optimization problem determined by an objective function for the process flow is given, is solved.
公开号:AT514225A2
申请号:T258/2014
申请日:2014-04-07
公开日:2014-11-15
发明作者:Johannes Willkomm;Matthias Wahler
申请人:Bosch Gmbh Robert;
IPC主号:
专利说明:

f J f J V ··· I ···············································································································································································································
Control of variable speed variable displacement pumps using modeN based optimization
Description 10
The present invention relates to a method for controlling a pressure medium supply for at least one hydraulic actuator and a computing unit for its implementation.
Prior Art 15
Pumps on which the invention is based consist of a variable-displacement pump per working cycle (so-called hydraulic displacement machine, for example a radial-piston or axial-piston machine), which is driven by a variable-speed drive. In the operation of such pumps, the volumetric flow 20 and / or the delivery pressure (i.e., pressure difference between inlet and outlet) are usually controlled by appropriate adjustment of the displacement volume of the conveyor and the speed, i. Such pumps have two degrees of freedom in the control.
In practice, it has proven to be problematic such a pump in the given case of application, i. So to operate an actuator in a - especially cyclically operating - machine to operate optimally.
In EP 1 236 558 B1 it is proposed to adapt the speed of the drive (in this case the electric motor) to the requested pressure or the requested volume flow. For this purpose, a speed profile is created in a learning cycle. This speed profile is used to change the speed during the course of the working cycles. To create the speed profile, a displacement volume profile for a variable displacement pump is first detected in a learning cycle at a constant speed of the electric motor. Subsequently, the constant speed and the displacement volume profile become a volumetric demand profile
Page 1 of 14 1/15 »·« 9 ··· ···· ·· ··· «··· · ·«
••• 9 ················································································································································································································ The speed profile is finally determined at a constant displacement volume of the variable displacement pump in DE 10 2009 018 071 A1, in which a limit displacement volume is additionally taken into account which is not to be exceeded when the speed is reduced
In DE 10 2011 119 299 A1, a control method is described in which the dynamics of a speed change is increased by rotational speed precontrol so as to counteract a delivery pressure drop with large changes in quantity. It remains desirable to be able to flexibly adapt the operation of a variable-speed variable-displacement pump to different applications.
DISCLOSURE OF THE INVENTION According to the invention, methods for regulating a supply of pressure medium for at least one hydraulic actuator and a computing unit for carrying it out with the features of the independent patent claims are proposed. Advantageous embodiments are the subject of the dependent claims and the following description. 20 advantages of the invention
The invention allows to flexibly adapt the pressure medium supply for at least one hydraulic actuator by means of a variable speed variable pump to different applications by a model-based setpoint specification for the pump. 25 The setpoint values for the control of the variable-speed variable-displacement pump are determined or calculated by solving a model-based optimization problem that is specified by an objective function, in particular under secondary conditions. It is essential that the target function for a procedure (characterized by setpoint trajectory) and not only for an operating point is specified. In particular, dynamic losses, which are caused by a change in the speed setpoint or the setpoint value for the parameter determining the displacement volume per working cycle, are taken into account in the target function.
Page 2 of 14 2/15 • ·
Η
• * ""·" · • ·· " ··· ..1
The model-based optimization itself is known. In this case, an extremum of a target function or quality function is determined. The objective function is derived from a model of the underlying system. According to a preferred embodiment, the model-based optimization problem is solved in the context of a model-predictive control (also referred to as Model Predictive Control - MPC).
The model predictive control itself is known. This is a control method that is particularly suitable for controlling nonlinear systems with multiple manipulated variables and for considering restrictions or secondary conditions. In addition to the one-time solution of the optimization problem, the current process actual state or actual state of the actuator (for example, speed, position) is now measured in each journal, and the optimization task with the current conditions is newly solved as input signal. A time-discrete dynamic model of the process to be controlled is used to calculate the future states of the process as a function of the input signals and to select suitable input signals on the basis of this prediction. This enables the calculation of the optimum input signal (in terms of the target function) while taking into account input and state limits. While the model behavior is predicted up to a certain time horizon N, usually only the input signal for the next journal is used and then the optimization is repeated. In this case, the optimization is carried out in the next journal with the then current (measured) process actual state, which can be regarded as a feedback and makes the MPC, in contrast to optimal controls, a regulation. This allows the consideration of disturbances.
Advantageous target functions in the control of a pressure medium supply are the most energy-efficient (i.e., with optimized efficiency) operation and the most dynamic, i. the specification as exactly as possible following, operation. In order to achieve the most energy-efficient operation possible, the model-based optimization preferably uses a loss model of the drive, conveyor and actuator, which is formulated and minimized depending on speed and tilt angle. In order to realize the most dynamic operation possible, the model-based optimization preferably makes use of a movement model of the actuator in order to detect a deviation between a desired movement and a desired movement
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• * ψ · · · ··· · I »· k ····· ··· # • ·«
Actual movement (ie a control difference) to minimize. Advantageously, a combined target function is provided, in which the described target functions each enter proportionally. In the combined objective function both energy losses and the control difference are included as costs. With slow movements, this variant will in principle correspond to the energy-saving scheme, since the control difference will virtually disappear. In highly dynamic movements, however, the control difference becomes dominant. In the case of combined optimization, a different weighting of the costs (energy losses and control difference) can also be carried out in order to adapt the regulation to the present needs. Possible advantageous constraints arise, for example, from the design of the machine and may include maximum input speed, maximum torque, maximum drive acceleration, maximum conveyor speed (e.g., swash plate pivot speed), maximum actuator speed, and so on. 15
In order to implement the model-based optimization control, it is expedient to transform the optimization problem to be solved into a standard form in order to be able to use common solvers. It has proven to be advantageous to express the objective function as a quadratic criterion, so that the resulting optimization problem can be treated as a quadratic program (QP). Particularly advantageously, the resulting optimization problem is treated as a quadratic program with one or more quadratic constrained quadratic programming (QCQP). 25 A computing unit according to the invention, e.g. a control unit of a variable-speed variable, is, in particular programmatically, adapted to perform a method according to the invention.
The implementation of the invention in the form of software is also advantageous, since this allows particularly low costs, in particular if an executing arithmetic unit is still used for further tasks and therefore already exists. Suitable data carriers for providing the computer program are, in particular, floppy disks, hard disks, flash memories, EEPROMs, CD-ROMs, DVDs and the like. It is also possible to download a program via computer networks (Internet, intranet, etc.).
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Further advantages and embodiments of the invention will become apparent from the description and the accompanying drawings. It is understood that the features mentioned above and those yet to be explained below can be used not only in the particular combination indicated, but also in other combinations or in isolation, without departing from the scope of the present invention. The invention is illustrated schematically by means of an embodiment in the drawing and will be described in detail below with reference to the drawing.
Description of the figures 15
Figure 1 shows a section of a hydraulic machine, which can be operated according to the invention.
FIG. 2 shows a control circuit according to a preferred embodiment of the invention. 20
Detailed description of the drawing
FIG. 1 schematically shows a section of a hydraulic machine 100, as may be the basis of the invention. The hydraulic machine has an actuator designed as a hydraulic cylinder 110 with a piston 111 that is movable along an x-axis, which is actuated by a variable-speed variable displacement pump 120. Between the variable-speed variable displacement pump 120 and the hydraulic cylinder 110, a hydraulic circuit 130 is arranged. The variable-speed variable displacement pump 120 has a drive designed as an electric motor 121 and a conveyor 122 designed as an axial piston pump in a swashplate design. A control unit 140 is set up by the program to carry out a preferred embodiment of a method according to the invention and specifies a setpoint speed risoii and a setpoint pivot angle erSoii. For controlling the manipulated variables,
Page 5 of 14 5/15 ····················································································································································································· This can be done using conventional sensors.
FIG. 2 shows a corresponding control circuit according to a preferred embodiment of the invention, as it may be implemented in the controller 140 in terms of programming. The control is based on a process 210, which specifies a setpoint motion target trajectory for the piston of the hydraulic cylinder 110. The movement
Target trajectories are usually time dependent and provide a motion profile r & // for the hydraulic cylinder 110 as a process target state and a velocity vSqii. The motion profile rson is transmitted to a control element 220, which here contains a model-predictive control as the preferred implementation of a model-based optimization.
As explained in more detail below, the setpoint speed nSoii and the setpoint pivot angle aSon are determined as part of the model predictive control 220. In particular, the movement profile comprises a time-dependent course of a position or position, speed, acceleration and / or force to be exerted or overcome by the piston 111 (so-called counter-force). In a known process can also be assumed that the counterforce over time is known. Thus, this can be incorporated directly into the optimization. In the case of previously unknown counterforce, this can be estimated (for example by extrapolation from past measured actual forces) in order to optimize the manipulated variables (rotational speed, swivel angle).
The actual speed and swivel angle control is realized here in each case by means of a PI controller 231 or 232, to which a control error (difference between setpoint and actual value) is supplied. The manipulated variable output by the controller 231 or 232 acts on the corresponding element (drive 121 and conveyor 122), which in turn act on the controlled system (hydraulic cylinder 110). From there, the actual values of the movement profile are traced as the actual process status and the speed vist. The actual state n "of the hydraulic cylinder 110 (position or position, speed, acceleration and / or force acting on the piston) enters the model-predictive control 220 as an input variable. The actual force can either be measured directly with a force sensor or calculated using a model from the known system pressure of the pump. In injection molding processes, e.g. Usually a p / Q nominal profile known or can at least be learned. The speed control loop can, for example, a cascade control of speed control and
Page 6 of 14 6/15 ····································································································· ··· «« «· ·« «· ·« · «* * * * # # ··
Include torque control, which serves as a manipulated variable beispielswese a drive current for the electric motor.
For correcting model errors and / or disturbance variables, the actual value of the speed Vist is offset with the associated desired value vSoii to form a further control error, which is supplied to a correction element 240. The correction circuit calculates a correction value for the target speed nSo "determined by the model predictive control 220 based on the speed control error. The correction element can be realized for example by a PI controller. Alternatively, the correction term may also be supplied to the desired swivel angle aSon determined by the model predictive control 220. In particular, this subordinate control loop does not require model knowledge and ensures follow-up behavior independent of model errors and / or disturbance variables. In addition to the speed, other process variables, such as the path or the pressure, can be used to calculate the correction term.
An alternative, equally preferred embodiment comes without the return of the
Actual state r / «off. In this case, the optimum values for speed and tilt angle are determined offline (or once online) and then used for process 210. A regulation or reaction to disturbances continues to take place here via the correction element 240.
Within model predictive control 220, the setpoints may be determined by minimizing an efficiency-optimized model, a dynamically-optimized model, and any combination of both.
The desired movement trajectories can be converted into an equivalent volume flow QSoii and an equivalent pressure pSo ", via which the rotational speed, swivel angle, load torque M and maximum displacement volume Vmax per revolution are linked to one another:
Qsoll ~ Should OfSoII Vmax,
Msoll ~ Psoll & Target Vmax / 2n
On this basis, a mathematical optimization problem with optional rotational speed or tilt angle can be used as a decision to carry out the given procedure.
Page 7 of 14 7/15 Ü ·· · · · ♦ · ·
•. Additional constraints can be formulated for the solution of this optimization task (see below). It is advantageous to transform the optimization problem into a standard form in order to be able to use common solvers. Advantageously, the constrained dynamic loss model may be formulated as a QCQP (Quadratically Constrained Quadratic Programming) problem. For a hydraulic cycle with the specifications
p (f Q {t) for t = 0 ... T can be the power loss Pvenust as a function of pressure p, volume flow Q, speed n 10 and swing angle a as: ^ loss,! ~ ^ Loss ,!
When calculating the power loss, the entire drive system consisting of frequency converter, motor and pump is taken into account. Preferably, further actuators 15 can be included in the consideration. Examples of losses are switching losses in the frequency converter, copper, iron and friction losses in the electric drive, as well as leakage and friction in the pump and other hydraulic components. The loss model can be based either on physical models or on experimentally obtained measurement results. For further details on losses in underlying pumps 20, see for example the publication " Investigations of Variable Speed Pumps " by Thomas Neubert, Shaker Verlag, ISBN 978-3-8322-0538-6. There, however, in contrast to the invention, no dynamic losses are considered, as they result in the control of hydraulic processes with non-constant setpoints for pressure and / or flow rate. For the model-based control concept on which the invention is based, in particular dynamic losses and transient transitions are taken into account. These arise, for example, when accelerating / braking the engine or adjusting the delivery volume per revolution of the pump.
This results in a loss over the entire process sequence (cycle t = 0... 7): 30 verl,, /, / ((0 "& < *) / 0 0, so that the to formulate the optimization task to be solved:
Page 8 of 14 8/15
T ···························································
min j WVerlus, = Σ ^ loss ,! (P (t), Q (t), n, oc)
loss
The dynamics-optimized model can be based on a movement model of the hydraulic cylinder, which transforms speed, acceleration and load / counterforce into equivalent nominal values for pressure and volume flow. In the following, a simplified model is given by way of example:
system
Where m denotes the moving mass of the piston FLast. counterforce
Azyiinder effective piston area
Eof. Modulus of elasticity of the hydraulic fluid
Vsystem total volume of the hydraulic fluid For the dynamics-optimized mode, in particular the below-mentioned secondary conditions are taken into account, so that it is possible to dispense with additional pilot controls as in DE 10 2011 119 299 A1. For a hydraulic process, the optimization task to be solved for the procedure can be derived as follows:
Herein, with the coefficients a and b, the deviations in pressure and volumetric flow can be weighted differently.
A combined optimization task can be represented as: min {A · WVerlusl + B · ^ Cycle] where with the coefficients A and B the losses and deviations are weighted differently.
For example, the following additional conditions can enter the optimization:
Page 9 of 14 9/15 ···· ·· • · ♦♦ · ···· «♦«
Climax speed limit Kl * «* acceleration limit ^ cycle, 11 ^ engine, max torque limit: Mcycle = M2) off, {p, Q, n, n, a) calculated via loss / motion model - < at < Relative swing angle Movement limit of the swash plate
Because the objective function is specified for a method sequence (in this case cycle 0... 7) and not just for one operating point, advantageously also dynamic losses, transient transitions and time-dependent secondary conditions can be taken into account. 5
In the case of operating-point-based concepts, the optimization task can always be carried out for a specific operating point in a single time step on the basis of the static analysis. On the one hand, this limitation means that a seemingly energy-optimal control of a process along a curve of statically optimized 10 operating points for speed / tilt angle in dynamic processes actually leads to an increase in the required energy due to the neglected dynamic losses. On the other hand, dynamic processes are lost in fast processes because, for example, in the case of volume flow jumps with an initially low engine speed and a small swivel angle, both rotational speed and swivel angle must be increased. 15
By considering a procedure, the two problems mentioned above are solved immediately. Energy efficiency is ensured by taking account of dynamic losses and the loss of momentum is offset by the integrated constraints. Decisive here are in particular acceleration, torque and 20 swivel angle positioning speed.
Dynamic losses Wet of the electric motor can be expressed for example with: (02 + fi *. Ges v kK {j dt
Page 10 of 14 10/15 ·· ·· ♦♦ ··
This designates
engine
Mges. Torque: Mges = (jMotor + ^ pump) ώ + -Mpra-asj J: moment of inertia ω: angular frequency MProcess load torque
Reu ', electrical resistance of the motor kM' · motor constant
The first term of the dynamic losses corresponds to the kinetic energy. When using a frequency converter with regenerative capability, this is not to be seen as a loss.
Dynamic losses Woynamik an axial piston pump in swash plate design can be expressed for example with:
+
This designates
Jsch & be '· moment of inertia of the swash plate A: piston surface of the adjusting cylinder for the swash plate x: distance of the piston longitudinal axis of the adjusting cylinder for the swash plate from the axis of rotation M {. torque applied to the swashplate by the actuator cylinder MReib: friction torque in the actuator cylinder
The friction torque for the adjustment of the swash plate can be determined empirically, for example.
Page 11 of 14 11/15
权利要求:
Claims (16)
[1]
·······································································································. 1. A method for controlling a pressure medium supply for at least one hydraulic actuator (110), by a variable speed variable displacement pump (120), in which a variable in a displacement volume per working cycle adjustable conveyor (122) by a variable speed drive ( 121) is driven, is supplied with a pressure medium quantity, which is determined by a predetermined pressure and / or volumetric flow profile, wherein a speed setpoint (nSoil) and a desired value (crSo, /) for determining the displacement volume per cycle Parameter for a procedure can be specified by a model-based optimization problem, which is given by a target function for the procedure is solved.
[2]
2. The method of claim 1, wherein the objective function is expressed by a quadratic criterion.
[3]
3. The method of claim 1 or 2, wherein at least one constraint is taken into account. 20
[4]
4. The method of claim 3, wherein the at least one constraint is expressed by a quadratic criterion.
[5]
5. The method according to any one of the preceding claims, wherein the optimization sample learning is solved as a quadratic program with at least one quadratic constraint.
[6]
6. The method according to any one of the preceding claims, wherein the objective function comprises a minimum power loss and / or a minimum control deviation. 30
[7]
7. The method according to any one of the preceding claims, wherein in the objective function dynamic losses, which are caused by a change in the Drehzahlsoilwerts (nSoii) or the setpoint (arSo ") for the displacement volume per cycle determining characteristic, are taken into account. Page 12 of 14 12/15 • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • ·· ♦ # ·· •
[8]
8. The method according to any one of the preceding claims, wherein the pressure and / or flow profile from a desired state (rsoii) of the hydraulic actuator (110) is determined.
[9]
9. The method of claim 8, wherein the desired state (rsoii) of the hydraulic actuator (110) comprises a position setpoint, a speed setpoint, an acceleration setpoint and / or a force setpoint.
[10]
10. The method according to any one of the preceding claims, wherein the model-based opti mierungsproblem is solved in the context of a model predictive control to which an actual state (r! S,) of the hydraulic actuator (110) is supplied as input.
[11]
11. The method of claim 10, wherein the model predictive control, an actual position value, 15 is a speed actual value, an actual acceleration value and / or a Gegenwirkistwert supplied as the actual state of the hydraulic actuator (110).
[12]
12. The method according to any one of the preceding claims, wherein a hydraulic cylinder with a movable piston (111) is used as a hydraulic actuator (110). 20
[13]
13. The method according to claim 12, wherein the speed command value (nSoii) is changed by using a speed command value (i / So ") and a speed actual value (vtst) of the piston (111) of the hydraulic cylinder.
[14]
14. arithmetic unit (140) which is adapted to perform a method according to one of the vorste existing claims.
[15]
15. Computer program with program code means which cause a computer unit to perform a method according to one of claims 1 to 13 when they are executed on the computing unit 30, in particular according to claim 14.
[16]
16. Machine-readable storage medium with a computer computer stored on it PATE PUCHBERGE A-1010 Wien Telefon 512 2

7 OS program according to claim 15. Page 13 of 14 07. April 20H 13/15
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公开号 | 公开日
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AT514225B1|2018-03-15|
引用文献:
公开号 | 申请日 | 公开日 | 申请人 | 专利标题

DE10110398A1|2001-03-03|2002-09-26|Mannesmann Rexroth Ag|Method for regulating the pressure medium supply to a hydraulically operated actuator|
US7849953B2|2007-11-29|2010-12-14|Caterpillar Paving Products Inc|Control system and method for operating a hydrostatically driven vehicle|
DE102009018071B4|2009-04-20|2011-12-29|Robert Bosch Gmbh|Method and control device for controlling a pressure medium supply for a hydraulic actuator|
DE102011119299A1|2011-11-24|2013-05-29|Robert Bosch Gmbh|Method for operating a variable-speed variable-displacement pump|DE102014001981A1|2014-02-17|2015-08-20|Robert Bosch Gmbh|Dynamic setpoint compensation for variable speed variable displacement pumps|
DE102018220505A1|2018-11-28|2020-05-28|Robert Bosch Gmbh|Model predictive control with improved consideration of restrictions|
DE102019220322A1|2019-12-20|2021-06-24|Robert Bosch Gesellschaft mit beschränkter Haftung|Method for operating a variable-speed variable displacement pump|
法律状态:
优先权:
申请号 | 申请日 | 专利标题
DE102013006137.7A|DE102013006137A1|2013-04-10|2013-04-10|Control of variable speed variable displacement pumps using model based optimization|
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