State Estimation for Controlling a Drive Machine Without Sensors

Abstract

Methods, apparatuses, and systems are provided for controlling an electrical drive machine. Actuator stator currents of the electrical drive machine are measured. A manifestation of an internal state of the electrical drive machine are estimated based on the measured actuator stator currents. A quality criterion is ascertained for the estimated manifestation of the internal state of the electrical drive machine. The estimated manifestation is forwarded if the quality criterion is satisfied.

Claims

1-12. (canceled)

13. A method for controlling an electrical drive machine, comprising: measuring actual stator currents of the electrical drive machine; and estimating a manifestation of an internal state of the electrical drive machine based on the measured actual stator currents.

14. The method according to claim 13, further comprising: ascertaining that a quality criterion is satisfied for the estimated manifestation of the internal state of the electrical drive machine.

15. The method according to claim 14, further comprising: forwarding the estimated manifestation of the internal state of the electrical drive machine if the quality criterion is satisfied.

16. The method according to claim 14, wherein the quality criterion comprises a comparison of the estimated manifestation of the internal state of the electrical drive machine with the measured actual stator currents.

17. The method according to claim 14, wherein the quality criterion takes into consideration a mean squared error and/or a total harmonic distortion of the estimated manifestation in order to assess a variance and/or a distortion of the estimation of one or in each case multiple parameters pertaining to the internal state of the electrical drive machine.

18. The method according to claim 13, wherein the estimation involves taking into consideration variances and/or covariances of the internal state of the electrical drive machine.

19. The method according to claim 13, wherein the internal state of the electrical drive machine is estimated using a nonlinear adaptive observer.

20. The method according to claim 19, wherein the nonlinear adaptive observer comprises an extended stochastic filter.

21. The method according to claim 13, wherein the estimation is performed based on one or more parameters pertaining to an operating state and/or an environmental state of the electrical drive machine.

22. The method according to claim 14, wherein the estimation is repeated for each of a multiplicity of successive sampling times, and the estimated manifestation are forwarded as soon as the quality criterion is or was satisfied.

23. The method according to claim 14, further comprising: determining a measure of quality for the satisfaction of the quality criterion.

24. An electronic control unit for an electrical drive machine of a motor vehicle, comprising: a sensor for determining actual stator currents of the electrical drive machine; and an estimator for determining manifestation of an internal state of the electrical drive machine, wherein the electronic control unit is configured to perform the method according to claim 13.

25. An electrical machine for propelling a motor vehicle comprising the electronic control unit of claim 24.

Description

BRIEF DESCRIPTION OF THE DRAWINGS

[0067] FIG. 1 schematically shows an electrical machine with an electronic control unit according to an illustrative example of the present subject matter.

[0068] FIG. 2 uses a flowchart to show a method for controlling the electrical drive machine from FIG. 1, the control being performed on the basis of a state estimation for the electrical drive machine.

[0069] FIG. 3 uses a flowchart to show a further method for controlling the electrical drive machine from FIG. 1, the control being affected on the basis of a direct triggering of the power switches of the inverter of the electrical drive machine.

[0070] FIG. 4 uses a flowchart to show a further method for controlling the electrical drive machine from FIG. 1, both method steps of the method from FIG. 2 and method steps of the method from FIG. 3 being used.

DETAILED DESCRIPTION

[0071] FIG. 1 shows an electrical drive machine AM for propelling a motor vehicle, not shown, said electrical drive machine being a separately excited three-phase synchronous machine having the phases L1, L2 and L3 in the example. It is irrelevant to the present subject matter and the example described here whether the synchronous machine is in separately or permanently excited form.

[0072] A drive battery B connects the machine AM to an energy source via a DC link ZK. The drive machine AM comprises an inverter having six power (half-bridge) switches S1, S2, S3, S4, S5, S6, which can be used to convert the DC voltage provided by the battery B into a three-phase voltage as specified by an electronic control unit SG.

[0073] The electronic control unit SG comprises measuring means 102 for measuring ACTUAL stator currents of the individual phases L1, L2 and L3. Furthermore, the electronic control unit comprises estimating means 104 (i.e. estimators) for determining manifestations of an internal state Z of the drive machine AM, computing means 106 for determining a respective DESIRED stator current for each of the phases L of the electrical machine AM, and actuation means 108 (in the example, as desired-current controllers for actuating the DESIRED stator currents). In addition, the electronic control unit SG comprises means for detecting a load requirement LW and/or boundary conditions RB during the operation of the drive machine, or the motor vehicle.

[0074] The internal state Z is defined in the example by the stator currents i and manifestations of the rotor angular velocity , of the magnetic flux and of the load torque T.sub.load of the drive machine AM.

[0075] FIG. 2 uses a flowchart to show an illustrative method 200 for controlling the electrical drive machine AM from FIG. 1, the control being performed on the basis of an estimation of the internal state Z of the electrical drive machine AM.

[0076] The illustrative method 200 has the following method steps: [0077] (S210) (in particular repeatedly) measuring the ACTUAL stator currents i.sub.a, i.sub.b, i.sub.c of the drive machine AM at a constant sampling frequency of for example 200 Hz. [0078] (S220) determining and providing the manifestations of multiple parameters pertaining to an operating state and an environmental state of the motor vehicle (referred to in combination as boundary conditions RB). [0079] (S230) the values ascertained method steps S210 for the stator currents i.sub.a, i.sub.b, i.sub.c and also the manifestations, associated with the sampling time, of the operating and environmental parameters from method step S220 are preprocessed, discretized and if necessary transformed, for example using a Carke transformation as shown in FIG. 1, in the estimating means 104 (inherently known to those skilled in the art) for subsequent use.

[0080] According to one example, this first involves the input currents being reduced from three to two. Based on these two currents, the further calculations are performed. The operating and/or environmental parameters RB from step S220 are taken into consideration for the estimation. The transfer to the estimator 104 is made in particular using a covariance matrix P.

[0081] Similarly, this step comprises initializing the estimator 104 with the suitably prepared values i.sub.A, i.sub.B, i.sub.C for the stator currents and RB for the boundary conditions of the estimation. [0082] (S240) estimatingi.e. forecastingan internal state Z of the drive machine AM on the basis of the measured ACTUAL stator currents i, which were measured in particular at the sampling time, using the estimator 104. [0083] (S250) correcting the estimator 104 (for the estimation that follows) on the basis of the state Z estimated in S240.

[0084] The estimator 104 is in the form of an adaptive, non-linear observer using an extended Kalman filter. In particular, a discrete-time extended Kalman filter is used that is tailored to the sampling times for the measurement of the ACTUAL stator currents. This facilitates an optimized software implementation of the estimation, which also facilitates sufficiently accurate estimation even using the limited computation capacities of control units customary in motor vehicles.

[0085] The observer 104 thus comprises a nonlinear extension of a stochastic filter and is implemented on the basis of a discrete-time nonlinear state model. The state space equations for the drive machine AM in this case are

{dot over (X)}=AX+BU

Y=CX+DU

[0086] The state model is initialized in accordance with step S230 using two covariance matrices Q.sub.0 and R.sub.0, which reflect the uncertainty of the estimation v(k) and the measurement w(k) (cf. step S231 in the detail representation of the observer 104 in the lower part of FIG. 2). The temporal discretization results in:

{dot over (X)}(k+1)=A.sub.dX(k)+B.sub.dU+(k)

Y(k)=C.sub.dX(k)+D.sub.dU(k)+w(k)

[0087] Here, A.sub.d is the system matrix and B.sub.d is the input matrix. C.sub.d and D.sub.d are the output matrices. These matrices can be resolved using a modified Euler method with the sampling time T.sub.s as follows:

A.sub.d=e.sup.ATsI+A*T+*T.sub.s.sup.2*A.sup.2

B.sub.dT.sub.s*B+*T.sub.s.sup.2*A*B

C.sub.d=C

D.sub.d=D [0088] I is a 66, unit matrix [0089] v(k) represents the uncertainties of the system with the covariance matrix Q.sub.0 [0090] w(k) represents the measurement noise with the covariance matrix R.sub.0

[0091] The estimation vector {circumflex over (X)}(k) for the four parameters stator current i, magnetic flux , rotor angular velocity co and load torque T.sub.load pertaining to the internal state Z of the drive machine AM, which are represented by six variables, is computed as (cf. step S241 in the detail representation of the observer 104 in the lower part of FIG. 2):

{dot over (X)}(k)=[{circumflex over (l)}.sub.s(k){circumflex over (l)}.sub.s(k){circumflex over ()}.sub.r(k){circumflex over ()}.sub.r(k){circumflex over ()}.sub.m(k){circumflex over (T)}.sub.L].sup.T.

[0092] As shown in step S242, a covariance matrix P(k) for the errors is also estimated by {circumflex over (X)}(k) and in step S251 the Kalman gain matrix K is estimated to project the residues onto the correction of the system state. In step S252, the output variables Y(k) are computed using the output matrices C.sub.d and D.sub.d.

[0093] (S260) comparing the state Z estimated in step S240 with the measurement of the stator currents i from step S210 and deducing from the comparison that a quality criterion QK for the estimation is satisfied. The quality criterion takes into consideration a mean squared error MSE and/or a total harmonic distortion THD of the estimation to assess the variance and the distortion of the estimation of the parameters pertaining to the internal state of the drive machine the estimator 104. (cf. step S261 in the detail representation of the observer 104 in the lower part of FIG. 2.)

[0094] (S270) forwarding the estimated internal state Z of the drive machine AM to the actuation means 108 if the quality criterion MSE or THD is satisfied. The DESIRED stator currents i.sub.desired of the drive machine are then actuated on the basis of the forwarded internal state Z of the drive machine AM.

[0095] The estimation of the internal state Z is repeated for each of a multiplicity of successive sampling times, and the determined manifestations are forwarded as soon as an estimation has been selected in respect of all constraints that need to be taken into consideration and/or the quality criterion is satisfied. This allows the algorithm to be trained quickly, improving the estimation result and the associated prediction of the internal state of the drive machine.

[0096] This allows reliable determination of the internal state Z of the drive machine to be attained by way of the estimation without an angle and/or rotation rate sensor for the position and/or rotation speed of the rotor.

[0097] FIG. 3 uses a flowchart to show a further method 300 for controlling the electrical drive machine AM from FIG. 1, the control being performed on the basis of direct triggers T for the power switches S of the inverter WR of the electrical drive machine AM by way of an actuation means 108.

[0098] The illustrative method 300 has the following method steps: [0099] (S310) determining an internal state Z of the drive machine AM. The estimation of the internal state Z of the drive machine AM from the illustrative method 200 shown in FIG. 2 can be used as a starting point or input variables for the method 300. As shown in FIG. 3, measured values from the drive can also be used instead, however. [0100] (S320) determining a propulsion requirement of a vehicle driver and thus a load requirement L compared with the load torque T.sub.load (that is to say in particular a load requirement L that leads to a load torque T.sub.load). [0101] (S325) determining manifestations RB of one or more parameters pertaining to an operating state and an environmental state of the motor vehicle. [0102] (S330) determining an internal DESIRED state of the drive machine AM on the basis of the determined internal state Z and the determined manifestations RB of the operating and environmental states. [0103] (S340/S350) determining multiple alternative sets, and multiple sets ascertained for successive sampling times, SVV of successively actuatable fundamental voltage space vectors V1 to V8, that for transferring the drive machine AM.

[0104] To reproduce a three-phase system, a half-bridge is needed for each of the three phases L1, L2, L3 (cf. FIG. 1). Each half-bridge can adopt two different switch positions for the power switches S1 and S2, S3 and S4, S5 and S6. Since three half-bridges are required for a three-phase system, this results in 2.sup.3 possible switch positions and therefore 8 switching states, which are referred to as fundamental voltage vectors V1 to V8. Each switch position yields a different voltage configuration between the phases L1, L2 and L3 and therefore also a different voltage space vector. The two switch positions for which either all three upper or all three lower switches are closed are an exception. These switch positions result in all three phases L1, L2 and L3 being shorted. It is therefore not possible to measure a voltage between the phases. These two voltage vectors are referred to as zero voltage space vectors. They can be used to represent 6 active and two passive fundamental voltage space vectors V1 to V8.

[0105] A suitable sequence of these fundamental voltage vectors V1 to V8 can be used to reliably set a desired torque T.sub.load as well as the desired rotor angular velocity . [0106] (S355) determining constraints on the actuation of the drive machine, for example and optionally inter alia from the boundary conditions RB and from limits for the motor operation of the drive machine. At least some of the following constraints are taken into consideration in the example: number of space vector changes, loading of the drive battery, drive temperature, weather conditions, etc. The constraints are inherently selected in a manner known to a person skilled in the art. [0107] (S360) taking into consideration at least one selection criterion AK, which is ascertained by a person skilled in the art from the constraints of S335, for the determined sets SVV of successively actuatable fundamental voltage space vectors V when selecting the set SVV to be actuated. The relevant selection criterion in the example may be one or more or all of the following typical constraints on motor actuation: number of space vector changes, loading of the drive battery, drive temperature, weather conditions, etc. In the example, the selection criterion AK is used for a cost assessment of the sets to be switched and for a switching loss assessment. [0108] (S370) actuating the inverter WR of the drive machine AM by way of the actuation means 108 with the selected set SVV of successively actuatable fundamental voltage space vectors using direct triggers T, which are delivered to GPOs of the actuation means 108 and transferred to the inverter WR.

[0109] The selected set SVV of successively actuatable fundamental voltage space vectors V is actuated using direct triggering (i.e. by way of direct triggers T) on interfaces of the power switches of the inverter WR of the drive machine AM. This allows hardware to be saved on account of there no longer being a need for a PWM unit and the associated timer.

[0110] The determination of the sets of successively actuatable fundamental voltage space vectors is repeated for each of a multiplicity of successive sampling times for the internal state of the drive machine. A selection is also made regarding whether a set used for actuating the drive machine is replaced by a set that was determined later, this selection being made in particular on the basis of the respective degree of satisfaction of a quality criterion QK. This promotes iterative, continuous optimization of the operation of the drive machine.

[0111] FIG. 4 uses a flowchart to show a further method 400 for controlling the electrical drive machine from FIG. 1, both method steps of the method 200 from FIG. 2 and method steps of the method 300 from FIG. 3 being used.

[0112] The output variables from the method 200 are used as input variables for the method 300.

LIST OF REFERENCE SIGNS

[0113] AK selection criterion [0114] AM drive machine [0115] B battery [0116] GPO general purpose output [0117] I.sub.a, I.sub.b, I.sub.c ACTUAL stator currents of the drive machine [0118] L1, L2, L3 phases of the drive machine [0119] LW load requirement [0120] QK quality criterion [0121] RB boundary conditions (parameters pertaining to an operating and/or environmental state) [0122] SG electronic control unit [0123] S1-S6 power switches of the half-bridges of the inverter [0124] Sxxx method steps [0125] SVV set of fundamental voltage vectors [0126] T direct trigger [0127] WR inverter [0128] Z internal state of the drive machine [0129] ZK DC link [0130] 102 measuring means of the electronic control unit for the stator currents of the drive machine [0131] 104 estimating means of the electronic control unit (estimator) [0132] 106 computing means of the electronic control unit [0133] 108 actuation means desired-current controller of the electronic control unit [0134] 200 first illustrative method [0135] 300 second illustrative method [0136] 400 third illustrative method