Template of Manuscripts for IREEbib.irb.hr/datoteka/425654.Clanak_ID_1666_IREE_final... · Web viewAdvanced Industrial Crane Controller Based on AC Wound Motor F. Kolonić, A. Poljugan,

International Review of Electrical Engineering (I.R.E.E.), Vol. xx, n. x

Advanced Industrial Crane Controller Based on AC Wound Motor

F. Kolonić, A. Poljugan, A. Slutej

Abstract –Developed speed crane control system which is based on a wound AC motor is an advanced system for heavy duty tasks especially in the field of industrial cranes and other heavy duty material handling systems. In order to avoid problems with a mechanical feedback device (coupling, vibration, no space for build in, etc.), actual speed information is calculated from a rotor voltage frequency estimation unit. The controller is developed as a modular system capable to deal with control, communication, protection and other specific industrial demands. It is a multiprocessor system in stand-alone version realized with microcontroller MC68332 (application program running), two SAB 82532 microcontrollers (distributing control system), two MC68302 (process I/O communication) and two DSP ADMC300 (speed and electromagnetic torque estimation). Speed and torque estimation algorithms are realized on the separate hardware modules and integrated with other components in the control system via fast communication link. Investigation of sensorless speed and torque control as well as fully automatic control of the rotor resistor switching, was the crucial point in the design process of a new industrial drive controller aimed mostly for the revitalization of industrial cranes. Performance of the speed and torque sensorless crane controller is evaluated on the laboratory testbed and in different real industrial environment.Copyright © 2007 Praise Worthy Prize S.r.l. - All rights reserved.

Keywords: crane control, revitalization, rotor frequency measurement, speed estimation, torque estimation, wound AC motor.

Nomenclature

- non-filtered (measured) rotor voltage of the U, V, W phase

- filtered rotor voltage - estimated rotor voltage frequency in the

low frequency operating regime- cut-off frequency of the rotor voltage LP

filter- rotor frequency estimation error- estimated rotor voltage frequency mean

value in high frequency operating regime- sampling frequency of a speed estimation- stator frequency- rotor frequency (measured, estimated)- frequencies of the rotor voltages U,V,W- current disturbance signal- stator current limit- stator current vector - stator current components in abc

stationary frame- α, β components of the stator current

- percent change in resistor value caused by temperature

- rotor contactors- speed level for frequency measurement

method switchover- calculated rotor speed of the last sampling - synchronous mechanical rotor speed- rotor mechanical speed- number of pole pairs- cable resistance, from rotor to ext. resistor - ith external rotor resistor value in cold and

warm case - rotor phase resistance- stator phase resistance- external rotor resistors- equivalent motor unity resistance- motor slip- rated (nominal) slip- sign of the motor slip (oversynchronous “-“- sign of the motor torque- maximal slip for ith external rotor resistor

for cold and warm case

Manuscript received January 2007, revised January 2007 Copyright © 2007 Praise Worthy Prize S.r.l. - All rights reserved


- possible motor torques in cold and warm case

- the number of pulses between two consecutive zero voltage crossing of the rotor phase U,V,W

- maximal motor torque for ith external resistor

- voltage disturbance signal- stator voltage vector- stator voltage components in a,b,c

frame- α, β components of stator voltage

- stator flux vector

- α, β components of stator flux

I. IntroductionIn the last fifty-sixty years AC wound motors have

been widely used in many industrial tasks, such as material handling systems, pipe and paper mills, steel and rolling mills, container loading/unloading cranes, power plants, engineering workshops, etc. In the beginning, the control of these drives was mainly focused on the rotor motor side using speed based rotor contactor switching for discontinuous additional external rotor resistor change. Thanks to that, it was surely the unique electrical AC machine at this time, capable to start with maximal available torque and at the same time drawing the minimal stator current from the mains. At that time it was a very pragmatic solution to use AC wound motors for those tasks, because of its high robustness and very simple and effective speed/torque control from the rotor side. Emerging power electronic switches, especially thyristors, with an additional AC/AC converter in the stator side, AC wound motors have got a new perspective in the control domain. Since the basic phase thyristor control from stator side is not satisfactory (limiting control region app. 10 to 30% around the nominal speed), the resistor control from the rotor side was added which resulted in outstanding features. With appropriate external rotor resistors switching and phase control of the stator voltage, all working points within the nominal speed and torque of four quadrant (4q) operation can be reached. The history of such controller type started in 1970's, when the Swedish company ASEA developed analogue ASTAT controller specially intended for the material handling crane purposes, [1]. It was designed for heavy duty installations with static components which required less space than a comparable relay based systems for the same purposes and with tachogenerator connection for the speed control loop. The voltage and current ratings were 3x220-3x500V and 18A-1700A. All the control electronics were in modular exchangeable circuit boards and the system was proven

in more than 6.000 installations. Controller had all needed function for the crane

applications but suffered in the lack of flexibility (controller’s parameter change), pure communication and monitoring capabilities, and from time to time had problems with components sensitivity due to the hard environmental conditions (temperature, dust, humidity). Afterwards, Siemens designed the SIMOTRAS HD crane controller with voltage and current ratings from 3x220-3x500V and 60A-900A, [2]. It was characterized with identical functions as ASTAT®, but built in a new technology, on the same platform as SIMOVERT Masterdrives and SIMOREG DC MASTER for DC drives. It uses tachogenerator and pulse encoder as speed feedback devices. The communication with the controller is realized via PROFIBUS-DP and as a user interface it’s possible to use operational panel OP1S or PC-program SIMOVIS. Comparing to the old analogue ASTAT® version, the advantage is more flexibility, in user interface and in communication capabilities with other devices in complex automation process.

The age of digital technique gives completely new dimensions in the crane control possibilities. Request from unavoidable industrial automation in the complex industrial systems resulted in the use of smart components for every specific function in the frame of complex industrial task. Considering the crane control issues, the requests are very large. With the new technical age, the crane controller has to be seen as an open control system from outside. Recognizing that, some OEMs (Original Equipment Manufacturers) developed new generation of crane controllers based on the wide spread AC wound motors, intended not only for the new drives, but for a revitalization of the old drives too.

The Purpose of revitalization is not only to extend the lifetime of electrical equipment, but also to include such control systems with new equipment on the global trend towards information systems which see cranes as crucial components in different industrial applications, e.g. material handling systems, container loading/uploading etc.

The crane’s logistic information system is more and more used for production cranes. The overriding level has to know precisely where materials (or cranes) are located and has to perform all operations quickly, consistently and reliably, [3],[4]. It is used for production orders, crane condition monitoring as well as for the set-up of crane motion controllers. The requests on the new advanced crane controller (revitalized or new) to communicate with an existing or new plant management system must be fulfilled.

The Swedish company ABB together with the Faculty of Electrical Engineering and Computing, University of Zagreb (Croatia) has developed the first version of the new digital ASTAT® crane controller in the beginning of 2000, [5]. The first installed digital ASTAT® controller was in EOT (Electric Overhead

Copyright © 2007 Praise Worthy Prize S.r.l. - All rights reserved International Review of Electrical Engineering, Vol. xx, n. x


Travelling) hoist crane in Husum paper mill (Sweden) in 2000. Today, the improved version of this controller type is the most advanced controller in the field of crane control with AC wound motor, where the speed and torque control can be performed without mechanical sensors. Some industrial applications, which are supported by this controller, show diversity of functions. For example, 16t and 170t hoist cranes in nuclear plant Forshmark (Sweden); 5 winch coordinated drive for power fleet mining mooring system with 80kw motors (Bangka, Indonesia); electrical shaft in steel factory Avesta (Sweden); 2 EOT ladle cranes; 3 planetary gearbox drive for 450t/80t (1.4MW) ladle hoist in BaoSteel, Baoshan steel making plant (China), etc. Some of these applications use estimated speed and/or torque feedback for the main control tasks.

II. Control System DescriptionThe structure of the developed controller is

presented in Fig. 1. Application program is running on the Main control board in Control module, built up around the Motorola MC68332 microcontroller unit and supported by a local operating system. The Main control board exchanges data with process by Process units (one unit is in Main control board, two process units are Cabin unit No.1 and No.2.). It is possible to connect up to 16 process I/O (Input/Output) units to the Main control board, [3], [4], [6].

The frequency of the rotor voltage (needed for speed estimation and presented in Control module as Rotor frequency estimation unit, Fig.1.) is determined by advanced digital filtering. Electromagnetic torque estimation is realized in Torque estimation unit in the same Control module. Estimated torque is used as actual torque for the torque control loop. For actual speed detection in oversynchronous regenerative mode of operation when speed sensorless control is used (no mechanical speed feedback), the sign of torque is used for accurate oversynchronous speed determination. In order to find optimal rotor resistor for each working point, automatic on-line rotor resistor optimization requires actual torque calculation too. This optimal resistor switching logic will be explained in details in chapter V.

By means of a thyristors pairs in each phase, stator voltage is continuously controlled with AC/AC phase controlled thyristor converter, Fig.2, [7]-[9]. The Main control board sends the firing pulses to the Firing unit in Thyristor module. Using five thyristor pairs (three pairs in each phase and two pairs for reversing), four quadrant operation is realized, Fig.2. Forward torque direction is defined by thyristor pairs 1, 2 and 3 (forward bridge) and reverse torque direction by 1, 4 and 5 thyristor pairs (reverse bridge). In the hoist type of motion, when the drive is lowering the load, motor may regenerate energy back to the line in

the most robust manner. Due to the safety reasons, the rotor resistor is minimized in this control region, ensuring regenerative mode with slightly higher motor speed than synchronous and the special open loop control routine is then activated bypassing outer speed control loop, [9].

Fig.1. The block structure of industrial crane controller

The Main control board communicates with all other units in the drive controller and includes all usual function for crane control such as joystick handling, limit switch logic with slow down and stop, automatic brake application approaching zero speed, automatic rotor contactor switching logic, etc.

All control system connections to high automation level (Master/Follower, Motion control, Overriding control communication), and Process control (including cabin I/O communication) are made by optical fiber. The communication is realized by two communication microcontrollers SAB82532. Details can be found in [3]-[6].

a) b)Fig.2. Four quadrant AC/AC thyristor converter a) and torque vs.

speed drive characteristics b).



With such controller design applied for revitalization, all requirements are fulfilled for the integration of these drives in the CDA (Complex Distributed Application), based on the crane control network facilities, [10].The general description of the speed control system is presented in Fig.3. The inner current control loop is subordinated to the outer speed or torque control loop, selected via parameter. Controllers are generally PID

type, with parameters and structure dependent on the specific industrial applications. Usually, reference value can be sent from master or cabin I/O units using joystick, or from overridden system via communication link. Optionally, speed feedback can be pulse encoder (E), tachogenerator (TG) or estimated speed (soft speed sensor). Considering nonlinear relationship between motor torque and current, nonlinear compensation block is added.

Fig.3. Simplified control block structure of industrial crane controller based on the wound AC motor The automatic on-line rotor resistor optimization algorithm, i.e. rotor resistor switching (selection) logic, insures minimal stator current taking into consideration the momentary line voltage and required torque. Plug braking and oversynchronous regenerative braking in hoisting mode is possible.

In short, this controller is like a modern car; the control system insures cruise control (stator voltage control) and automatic gearbox (optimization of rotor characteristics).

III. Basic concept of a speed estimationIn order to avoid mechanical speed sensor or/and

ensure a speed measurement devices redundancy when mechanical speed sensor exists, the speed estimation system was developed. Before speed estimation process analysis it has to be emphasized that design process is based on a strictly defined industrial sponsor’s requests frame. This frame summarizes the following issues:

AC wound motor as the actuator for the crane drive applications,

Realization of the stator voltage control by means of AC/AC 4q thyristor phase converter,

Optimization of the speed-torque characteristics by means of the external rotor resistors change,

Speed and torque estimation logic as a separate plug-in unit (according to modular design strategy).

The speed and torque estimator are developed using a DSP based microprocessor boards in order to fulfill signal processing requirements, Fig.4. These boards are integrated in the modular structure of the industrial control system via I/O unit using high speed serial link RS422 (speed 1-4Mbs).

Fig.4. The speed and torque estimator boards (hardware realization); speed estimator (upper board), torque estimator (bottom

board)Considering the speed estimation, the conventional

techniques used for the vector controlled squirrel cage induction machine (Field Oriented Control, FOC) can



not be used in this application. That is why different solutions for the speed estimation considering the above defined sponsor's requests frame were needed. Since a wound motor is used, rotor voltage can easily be measured on the rotor rings, [11]. The idea for the speed estimation can therefore be described with the simple well known relations,

(1)

III.1. Rotor voltage frequency measurement

Because the large amount of higher harmonics produced by stator phase controlled AC/AC converter is transformed on the rotor, low pass rotor voltage filtering must be applied to the rotor voltage frequency estimation. This is connected to the desirable frequency (speed) estimation accuracy. Rotor frequency is determined by measuring the time period between two consecutive zero passing of the filtered rotor voltage waveform. For specific drive operating conditions (e.g. reversing from over synchronous regenerative speed), the frequency of the rotor voltage may be approximately

between 0-120 Hz. That is the reason why the adaptive filter was designed. The filter selects appropriate cut-off frequency, based on the speed estimator output value, Fig.5.

Fig.5. Block structure of the realized variable rotor voltage filtering

The presented filter is variable in the sense of cut-off frequency change, but the filter structure, type and order remains unchanged. The base structure of the variable filter is the cascade of the three 1st order low pass (LP) filters. The main criterion for the selection of an appropriate cut-off frequency fc is the calculated rotor speed of the last sample nfilt, Fig.5, and Fig.6., [9].

Fig.6. Simplified block diagram of the frequency (speed) estimation algorithm



a)

b)Fig.7. Original and filtered rotor voltage waveform with frequency

20Hz a) and 41HZ b).

Based on the comparison between the estimated speed absolute value and predefined value, the selection between the two filter cut-off frequencies is provided by signal selector low_freq, Fig.5. There is a possibility of a more cut-off frequency values selection, but applied testing shows that the increasing number doesn’t improve considerably estimation performance, [12]. Results of filtering for the rotor voltage frequencies 3,5 Hz and 41 Hz is shown in Fig.7.

If the drive operating points result in the rotor voltage frequencies lower than a predefined limit (signal nlev, Fig. 6.), another frequency estimation algorithm will be activated. It is achieved by the same low_freq selector, in the block Rotor frequency measurement in the LOW frequency operating regime, see Fig. 6. In this algorithm rotor frequency measurement is based on the time distance between two consecutive zero voltage crossing of all three rotor phases (signal fALL_PHASE). For the high rotor voltage frequencies region (e.g. over 25 Hz, close to the rated condition) frequencies for each rotor phase f2U, f2V and f2W are calculated from non-filtered rotor phases E2U, E2V, E2W, and the mean value estimated frequency fMEAN

is derived. The zero rotor voltage passing is determined by a

positive derivation block which produces impulses for time counter, Fig.6. Then the frequency of the rotor voltage is calculated according to the equation

. (2)

The sampling frequency of the rotor and stator frequencies measurement unit is 10 kHz, so the estimation error with cycle ΔT=0.1ms is

. (3)

The error is directly proportional to the frequency, e.g. if the estimated frequency is 100Hz, error is 1%.

For the low rotor voltage frequencies (less than 25 Hz), time between two consecutive zero passes (positive and negative) of any rotor voltage (U, V or W) is measured and estimated frequency fALL_PHASE is derived. This modification provides six times faster refreshment of the frequency (speed) estimated value, which is important for the stability of the speed control loop. For example, if the rotor voltage frequency is 5 Hz, then refreshment time (time needed to establish new estimated value) will change from 200 ms to 200/6= 33,3 ms. The illustration of the rotor voltage frequency measurement modification is shown in Fig.8.

Fig. 8. Illustration of the rotor voltage frequency measurement

modification

Based on the Fig.6, the frequency estimation algorithm is experimentally verified on the speed control system, Fig. 9, where the speed reference is changed from +nmax to -nmax. The frequency change is close to 100 Hz (maximal slip is s2). One can notice that the rotor voltage frequencies before and after speed reversing are practically the same, but the speed values have different sign. This indicates that for speed determination some drive condition signals have to be used in order to establish exact speed values. Block diagram of the rotor voltage frequency estimation realized with digital signal processor ADMC 300 is presented in the Fig.10.



Fig.9. Estimated rotor voltage frequency under full speed reversing (from +n_max to –n_max)

It is possible to estimate frequency and speed for 4 motors at the same time. After the first stage of analogue signal processing and A/D conversion in the second stage, digital filtering of rotor voltages is performing in the third stage. After that, information is sent to the Process I/O unit via fast serial RS422 link, see Fig.1.

Fig.10. Block diagram of the rotor voltage frequency and speed estimation realized with digital signal processor

III.2. Rotor speed measurement

It is simple to calculate the estimated speed from the estimated frequency (2) by knowing the right position of motor operating point inside 4q operation region of speed/torque characteristics. Actual motor speed is calculated using equation

.

(4)Characteristics of the speed estimator for 10% and 100% square wave speed reference in both directions are presented in Fig.11. and Fig.12. The comparison between speed signal from tachogenerator (TG) feedback device and estimated speed from the rotor voltage frequency measurement has been experimentally performed. The experiment is based on the control scheme in Fig.3, where the speed control loop is closed with the mechanical feedback sensor (TG). As it can be seen from experiments in Fig.11. and Fig.12, the speed estimation error in steady state is smaller when the speed reference is set as +100% (-100%) than +10% (-10%). Speed error is larger in transient state in both cases; it is due to the inherently slow process of the frequency estimation which increases refreshment time of the new estimated frequency value.

a) b)

Fig.11. Estimated (1) and measured (2) speed a), estimated speed error b) for 10% speed reference (150 rpm)

Speed(RFM and TACHO)

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0

500

1000

1500

0.1 2.9 5.8 8.6 11.5 14.3 17.2

time(s)

spee

d(r/m

in)

Speed error (wRFM-wTACHO)

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c) d)


SPEED [rpm]

(1)

(2)(1)

(2)

SPEED ERROR [rpm]

SPEED [rpm] SPEED ERROR [rpm]

time [s] time [s]

time [s]time [s]


Fig.12. Estimated (1) and measured (2) speed a), estimated speed error b) for 100% speed reference (1500 rpm)

The speed estimation equation (4) is valid as long as the rotor voltage frequency is properly estimated. There are three basic (specific) operation states where 4q speed control system, based on the estimated speed, doesn't work properly. Those are: AC/AC converter dead time (switch-over state), operation region with small load and operation region with small slip (close to synchronous).

For the purpose of accurate speed estimation in the all operating regimes, the speed estimation freezing logic (SEFL) is designed, Fig.13. It should be emphasized that the proposed logic can eliminate all influences caused by specific operation states on the estimated speed accuracy. The estimator output nest is frozen every time when the new speed estimated value is physically unacceptable. Physical acceptability means that the difference between two consecutive samples of the estimated speed cannot be significantly large (a few percent of the estimator output value).

Fig.13. Simplified block diagram of the speed estimation freezing logic (SEFL)

If acceptability condition is not fulfilled, the new estimated value is rejected and the estimator sets the old estimated value on its output (frozen state). However, for the safety reason, estimator output unfreezes when the maximal allowed freezing time is exceeded and/or the rotor voltage amplitude increment is detected. The rotor voltage amplitude increment implicates the machine torque increment and, as a consequence, the operating point changes. The comparison between the estimated speed with and without SEFL in the case of speed reference change from 1500 rpm to -1500 rpm is presented in the Fig.14. When the speed reference command for opposite direction is set (t=3.3sec, see Fig.14.), subordinated current controller requests negative torque, i.e. switching from forward to reverse thyristor bridge in AC/AC converter, see Fig.2. This logic, very similar to AC/DC dual converters for DC drive, leads to unavoidable converter’s safety dead time (10ms), which results in a rotor voltage frequency estimation error and consequently speed error too. One can see from the Fig.14 that the estimated speed (red line) has a large dynamic error in the moment of the speed

reference change, as opposed to SEFL (green line), which works correctly.

rasterećenje (s ~50% Mn na 0)

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0,5 1 1,5 2 2,5 3 3,5 4 4,5 5 5,5 6 6,5 7 7,5 8 8,5

n_taho [rpm] n_est_noFIFO [rpm] n_est [rpm] n_ref [rpm]

b) rastrećenje

a) reverziranje

t [s]

t [s]

n_est_nofreeze

Fig.14. Comparison between estimated speed with (green) and without (red) use of the output freezing logic in the case of speed

reference change (from 1500 rpm to -1500 rpm)

Unloading the machine from ~50 % of Tn to zero, leads to a similar problem, Fig.15. Because of the speed increase, control system requests reverse torque in order to equalize reference and actual speed value. After the control system processing time, which includes converter's dead time, reverse bridge is turning on and speed control starts. Due to the problem of rotor frequency estimation during converter's switching dead time, speed estimator gives incorrect value on the output in the first moment after dead time elapse, see Fig.15.b). However, owing to the proposed freezing logic (SEFL), accurate estimated speed value is attained.

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-1200

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600

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0 0,5 1 1,5 2 2,5 3 3,5 4 4,5 5 5,5 6 6,5 7

n_ref [rpm] n_taho [rpm] n_est_noFIFO [rpm] n_est [rpm]

rasterećenje (s ~50% Mn na 0)

b) rastrećenje

a) reverziranje

t [s]

t [s]

unloading(from ~50% to 0% Mn)

n_est_nofreeze [rpm]

a)

b)Fig.15. Comparison between estimated speed with (green)

and speed without (red) SEFL in the case of the machine unloading a); enlarged part b).



IV. Basic concept of a torque estimationIn order to fulfill the control system application requirements as well as to achieve system competitiveness a torque control loop was added, Fig.3. The estimated torque is important variable for the speed estimation and for the automatic on-line rotor resistor optimization.

The use of conventional methods for measuring torque on the shaft coupling a motor to a load by means of strain gauges yields to the accurate values for a constant or slowly varying torque. Furthermore a mechanical sensor must be selected according to the motor's speed and size. This can be difficult and expensive if you work with a variety of motors at the site testing, where installation and mounting of mechanical sensors could be very costly and time consuming. Also, sometimes the site is difficult or dangerous to access and it may not be practical to install a mechanical measuring sensor for torque as well as for speed measurement.

The described solution of dynamic torque measurement does not need any mechanical elements. The algorithm of the electromagnetic torque estimation is based on the estimation of the stator flux in the stationary reference frame (- frame). The instantaneous values of the stator voltages and currents are measured and the stator flux is calculated using voltage equation

.

(5)

From (5) follows the stator linkage flux

. (6) Based on the (5) and (6), - components of the stator linkage flux Ψs (Ψs , Ψsβ) are calculated as

,

(7)

.

(8)

For "Y" stator windings connection, - components of the stator voltage and current are calculated from measured a-b-c components as

, ,

(9)

, ,

(10)

and for the "" connection respectively

, ,

(11)

, .

(12)

From (1) to (5) yields final expression for the electromagnetic torque.

. (13)

Before the real time implementation, mathematical model of induction motor with short-circuited rotor in - coordinate system is realized and tested in Matlab/Simulink in order to test the validity of model described by (5)-(13).

Fig. 16. Speed response under sine-wave voltage step reference

Fig. 17. Estimated electromagnetic torque response under sine-wave voltage step reference

Step responses with sinus-wave stator voltage supply and nominal load step (75Nm) in t=0.6 s are presented in the Fig.16. and Fig.17. The simulation results show validity of the model described by (5)-(13), with ideal sinus voltage supply and short-circuited rotor. Real-time torque estimation performance will be presented in the section VI with experimental results.


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[Nm]

[s]

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[s]


Considering real time application, it is important to emphasize that special attention has to be paid to the flux calculation (6) in order to suppress any offset in the numerical integration without influencing the current and voltage aperiodic components, [13]-[16].

The flux estimator defined with (6) is referred as the stator voltage model. This model is difficult to apply in practice since unavoidable disturbances in voltage and current, ud and id, are superimposed to the ideal measured signals, us and is, Fig.18. Typical examples of those undesirable effects are offset and drift which originate from analogue signal measurement. Experimental results with estimator in [16] show that the ideal estimation is possible only if the stator resistance Rs of the estimator is identical to the estimated (measured) resistance of the machine and if the measured current and voltage are without any errors such as noise or offset errors. This ideal estimation is happening even though the rotor current differs from zero.

In order to avoid the stator flux drift and saturation, the integrator in (6)-(8) is replaced with an adequate filter, Fig.18, [15]. Using the filter instead of integrator, low frequency signal (i.e. dc signal) will be attenuated, but the high frequency signal (ac components) will be not affected.

Fig.18. Calculation of the stator flux using filter instead of pure integration

As one can see from Fig.18, only electrical stator values are needed for the electromagnetic torque calculation. The difference between the obtained electromagnetic (air gap) torque and the mechanical (shaft) torque is in the losses originated from friction, bearings and ventilation, which are mainly a function of the speed. These quantities can be determined during a no-load run of the machine.

Functional block diagram of electromagnetic torque calculation realized on DSP ADMC300 is presented in Fig.19. After voltages and currents signal processing in DSP, information of electromagnetic torque is sent to the overriding system by the fast serial link RS422.

Fig. 19. Block diagram of the electromagnetic torque estimation

realized with digital signal processor ADMC300

V. On-line rotor resistor automatic optimization

In order to achieve effective speed control, rotor resistor optimization logic is added. This logic changes the amount of the external added resistance in the rotor circuit by means of the rotor contactors, Fig.1. Proposed optimization logic minimizes the stator current of the motor, taking into consideration the momentary line voltage, required torque and resistors value tolerance. In each sampling time at the momentary motor speed, optimization algorithm calculates maximal torque produced for each external rotor resistor. Among all calculated torques available for each additional rotor resistor, one resistor (the best in optimality sense) will be chosen and connected to the rotor by means of contactor. All contactors are handled by digital outputs (DO) of the process I/O board, Fig.1. The criteria for external rotor resistor selection can be defined in software, but usually the criteria is developed maximal torque. Using this algorithm, the start up adjustment is reduced, the motor can be used with a less stable line supply and it is easier to use existing resistors in revitalization tasks. The schematics of the 5 steps rotor resistors (R1-R5) with 4 contactors (K0-K3) driven by process I/O digital outputs (DO1-DO4) respectively is presented in Fig.20. The resistor value ΣR i in (14) has to be chosen according to specific industrial application. For different types of movements (e.g. hoisting, plug mode lowering, oversynchronous regenerative mode lowering, traveling, etc) the values suggested in [5] give trouble-free performance in most situations. Resistor value ΣRi is calculated as

,

(14)where R100 is unity resistance and defined as

.

(15)

Unity resistance is defined as resistance that will hold the motor at zero speed with nominal load and nominal voltage. The values 8, 18, 38, 65, and 100% of the unity resistance R100 have been chosen for ΣRi as



mostly used values in industrial applications. The resistors Rm and Rc are defined as

. (16)

Now all the elements for Ri calculation, based on (14), are noun. Influence of the resistor change in

dependence of the temperature, is considered through the following equations

,

(17)

.

(18)

Fig.20. Flowchart diagram of the automatic on-line rotor resistor optimization

Before the maximal torques calculation logic starts (Fig.20), mode of operation must be defined. This is because the rotor contactor logic is working in a different way for different modes. With the first decision block in flowchart diagram, it is assigned whether the drive is in a subsynchronous or in oversynchronous (plugging or regenerative) region. Drive mode is defined on the base of direction of the motion requested, direction of the field (converter state), type of the motion (hoisting potential loads, traveling reactive loads) and actual motor speed. The motor must be able to produce requested torque (TREQ); LIMP is assigned in Fig.20. as requested torque for positive and LIMN for negative mode. Then the possible motor torques for each Ri resistor at each speed for cold and warm state are calculated according to the following equations

,

(19)

.

(20)Here TiC and TiW are possible torques in cold and

warm state for i-th rotor resistor at slip s (as a multiple of nominal torque) and U and Ilim are supply voltage and current limit. At maximal (breakdown) torque TM, the values of slip in cold and warm state siWM and siCM

are defined as

,

(21)



.

(22)

What are the basics of the automatic rotor resistor optimization strategy? Check possible motor torques T5, T4,..,T1 in sequence to find a T i that is bigger than TREQ, Fig.20. As such Ti is found, the right external resistor (i.e. right contactor switching) is defined.

It is experimentally confirmed in the following section that the algorithm for on-line rotor resistor calculation has excellent features in all requested modes of operation and can replace successfully standard speed-based rotor contactor handler where contactor switching points has to be calculated in advance, each time for new industrial application. From an industrial point of view, this means no extra cost for additional commissioning caused by speed-based switching points determination.

VI. Experimental resultsLaboratory setup for experimental verification of the

system's performances is presented in Fig.21. (M1- wound AC motor: 3x380V, 38,5A, 18,5kW, n=1480 rpm; M2-DC motor, 220V, 91A, 17kW, n=1500 rpm; separate excitation). Target AC wound motor (M1) driven by developed controller ASTAT in speed control mode is mechanically coupled with DC motor (M2). The latter is driven by the SIMOREG controller in torque mode loading target AC motor.

Fig.21. Laboratory test bench for experimental verification

Experimental results have been performed mainly in the laboratory, but some of them in industrial environment too (at the site). For the program designed, data acquisition, measurement, monitoring and recording, two different platforms during the project design are developed. The first one is based on the microcontroller MC68332; PCASE tool for code design and ASTAT tool as monitoring, recording and Commissioning and Maintenance Tool (CMT) for the main application program design. The second one is based on the digital signal processor ADMC3000 with alternative tools for code design and CMT; CADSTAR and PARNAD [5].The latter platform is related to the speed and torque estimation tasks only.

In this chapter we would like to emphasize that the following tasks are realized in the design process of presented controller: speed control task in the industrial crane applications with mechanical sensor (tachogenerator /pulse encoder) and speed estimator; SEFL logic as effective method for accurate speed detection in the critical condition mentioned in the section III.2 (Fig.12); estimated electromagnetic torque needed for torque feedback loop, for accurate speed estimation and for automatic on-line rotor resistor selection.

One of the basic experiments is 4q operation in hoisting condition with potential load. The result of testing is presented in Fig.22. For the maximum trapezoidal-like speed reference in hoisting condition, drive with emulated load is accelerating with automatic external rotor resistors switching, which can be seen on the torque response particularly in the interval of 1-4s. Afterwards, the full speed reference for lowering a potential load in reverse current braking (plugging) mode is ordered. The load is lowering in non- regenerative mode with slip more than 200%! In this case the load is approximately 70% of nominal motor torque Tn; at the same time this is a maximal achievable load torque produced by the DC drive.

Fig.22. Estimated torque and speed feedback in 4q sub-synchronous

operation with potential load (typical hoist drive in crane applications)

The performances of the speed control loop with mechanical sensor and estimated speed (soft) sensor are presented in Fig. 23 and Fig.24. Recorded variables are, stator current is, rotor speed n2 and speed reference after prefilter n_ref_pf. The prefilter is added in the speed reference only for the laboratory testing. This is because the parameter of PID speed controller is determined through the Ziegler-Nichols closed loop test, where such obtained P and I gains result in high overshoot under step reference test. Fig. 23. and Fig. 24. present a speed control system with mechanical sensor and with speed estimator respectively under positive and negative speed reference step change in the range of 50-70-50% ns. It can be seen that the control system with speed estimator has expected inferior characteristics due to the inherent delay in estimator explained in section III.2. Introducing the rotor voltage frequency measurement modification, see



Fig.8, this delay is minimized, which enables application of proposed controller in large variety of industrial applications. It can also be seen that for the both alternatives, the control system considerable suppress disturbance caused by the rotor resistor change. The performance of the control system with tachogenerator (TG) as mechanical sensor in subsynchronous regime is presented in Fig. 25. It is hoist drive with active load, where the speed reference is trapezoidal-like and it is set by joystick. The shape of the reference can be defined in application software. In experiment a) active load is 23% of the nominal load Tn and in b) experiments the active load is maximal 70% of nominal load Tn. For the both experiments automatic on-line rotor resistor optimization is used. It can be seen after acceleration in forward direction that minimal forward torque is needed for braking and speed reversing in case a); practically, active load is enough to accelerate in reverse direction. Since the plugging mode has been chosen and reference speed is set as synchronous (ns), the controller keeps the actual speed value just as synchronous by means of forward motor torque. It

would be the same situation even for the maximal load torque. For b) case, only higher forward motor torque is needed to keep the lowering (synchronous) speed. When the drive lifts the load, speed error in steady state is proportional to the lifting load. This error is a consequence of the actuator saturation, because synchronous (maximal) speed is set as the reference speed. The automatic on-line rotor resistor optimization performance is presented in Fig. 26. For the regenerative mode selected, lowering speed is higher than synchronous and motor regenerate energy back to the mains. For this mode of operation special open loop logic is used which bypass speed controller, [9]. Active load is then tightly connected to the mains and designed control logic ensures bumpless return to the closed speed control loop with TG mechanical sensor. This experiment evidently confirms that automatic procedure for the rotor resistor selection works well. The experiments in Fig.27. show a good performance of the sensorless drive which uses estimated speed value based on the estimated rotor voltage frequency. In both experiments control system in lowering mode uses different active loads for regenerative braking.

Fig.23. Step response of the speed control system with mechanical sensor, speed reference 50-70-50% of synchronous speed.

Fig.24. Step response of the speed control system with estimated speed, speed reference 50-70-50% of synchronous speed.



a) b)

Fig.25. System responses for the speed reference profile (1500rpm, maximal), TG sensor, automatic resistor selection; plugging braking; active load; a)23%; b)75%; blue-ref speed and red-actual speed, 0,25ns/div; black-estimated torque, 0,5Tn/div; 2sec/div

a) b)

Fig.26. System responses for the speed reference profile (1500rpm, maximal), TG sensor, regenerative braking; active load 55%; automatic a) and manual b) resistor selection; blue-ref speed and red-actual speed, 0,25ns/div; black-estimated torque, 0,5Tn/div; 2sec/div

a) b)

Fig.27. System responses for the speed reference profile (1500rpm, maximal), speed estimator, automatic resistor selection; regenerative braking; active load; a) 23%; b) 55%; blue-ref. speed and red-actual speed, 0,25ns/div; black-estimated torque, 0,5Tn/div; 2sec/div



a) b) c)Fig.28. Testing at the site (Okselesund, Sweden, 80tones hoist drive), speed control system, speed estimator; regenerative braking a); plugging b);

Testing at the site , BaoSteel, Baoshan, China, 450 tones hoist drive, c); blue-ref speed and red-actual speed (0,25ns/div); black-stator current (0,5isn/div); green-forward and pink-reverse bridge; time scale1sec/div

The Fig.28. a) and b) present the results of the crane control system monitoring during the commissioning at the site. The first one is 80 tones hoist drive with speed estimator presented in regenerative a) and plugging b) mode of operation. The second one is 450 tones ladle hoist crane with mechanical sensor, Fig. 28.c). All recording has been performed by means of the CMT monitoring tool designed during this project.

VII. ConclusionWe would like to emphasize that the developed

control system is not a servo drive system! It is not designed for high precision speed control tasks. It is aimed prior for revitalization tasks of old drives based on the AC wound machine, but controlled by components based on the up-to-date technology. The proposed system provides safe, reliable and simple control in industrial applications such as heavy duty material handling systems, steel and rolling mills, container unloading and uploading cranes, power plants, etc. Our contributions in the design of proposed controller are expressed through the following issues: original rotor speed estimation technique based on the rotor voltage frequency estimation with implementation on the industrial crane controller (method and device patented!); related to the speed estimation, nonlinear estimation freezing logic (SEFL) is designed for accurate speed estimation in the operating region where the rotor voltage signal is not acceptable for accurate frequency estimation (AC/AC converter dead time, operation region with small load and with small slip); implementation of the electromagnetic torque estimator, based on the stator voltages and currents measurements, needed for accurate speed estimation, for automatic on-line rotor resistor selection and for the feedback sensor in the torque control loop; original algorithm for automatic on-line rotor resistor optimization logic which selects

rotor resistor in order to get maximal developed motor torque at each microcontroller’s sampling time.

It is experimentally confirmed on the laboratory test bench and through recording at the site, that speed control system with soft sensor achieves good performances. SEFL logic involved in the control approved the safe operation which has been attained in all operation modes, especially in the regenerative mode of operation, which is particularly important in the hoist crane drives. The experiments confirmed good functionality of the speed open-loop logic in the regenerative mode owing to the bumpless technique we applied. The process of energy recuperation is very simple and more effective than in the case of a frequency controlled AC squirrel cage motor supplied by inverter.

The experimental tests of the automatic on-line rotor resistor optimization logic confirm excellent features in the all requested operating modes and proposed logic can replace successfully standard speed-based rotor contactor handler. Comparing to the classical (manual) speed-based rotor resistor switching, there is no considerable difference in performances in the first moment. However, in speed-based rotor contactor logic switching points have to be calculated in advance, each time for the new industrial application, which leads to extra cost for additional commissioning.

Within the development of the advanced industrial crane controller based on the AC wound machine, we have designed a modular system capable to deal with control, communication, protection and other specific industrial demands. Such controller, either as new drive or revitalized, can be integrated as a client in the control network, used in crane motion concept with digital drive controller system.

Acknowledgement



The project of industrial controller (with commercial name ASTAT®) is a result of joint cooperation between the Faculty of Electrical Engineering and Computing, the University Zagreb (Croatia) and the Swedish company ABB, and it is financially supported by ABB. As a result of this cooperation, over 3000 industrial applications, especially in the crane and other heavy duty material handling systems are installed all over the world.

Based on our investigation of the crane control system related to the sensorless speed control technique, our industrial partner ABB patented the method of speed estimation:Patent No: WO01/27637 Device and a method for estimating the speed of a slip ring asynchronous machine

References

[1] ….., ASTAT, Semiconductor controller for slip-ring motors Manual, ABB Industrial Systems AB, Crane & Harbour Systems, ReklamCenter AB (6032), Västerås, Sweden, 05/1996.

[2] ….., SIMOTRAS HD – Der neue Drive für Krane mit Schleifringläufermotoren, Excellence in Automation & Drives, Siemens, Erlangen, 04/1999.

[3] A. Slutej, F.Kolonić, Ž.Jakopović, The new crane motion control concept with integrated drive controller for engineered crane application, Proceedings of the IEEE International Symposium on Industrial Electronics, ISIE’99, July 12-16, 1999. Bled, Slovenia.

[4] A. Slutej, F. Kolonić, Control network as a backbone of the crane motion control system, Proceedings of the 10th EPE-PEMC 2002 (CD ROM), September, 9-11, 2002,Dubrovnik, Croatia.

[5] ...., ASTAT Crane Motion Control, (CD-ROM), Manual, ABB Automation System, 2003.

[6] A. Slutej, L.T. Hansson, F. Kolonic, Steel mill crane motion control with a new integrated drive controller, Proceedings of the 10th International Symposium EDPE’98, October 14-16, 1998, Dubrovnik, Croatia

[7] N. Mohan, T.M. Undeland, W.P. Robins, Power Electronics: Converters, Applications and Design (John Wiley and Sons, 1989).

[8] B.K.Bose, Power Electronics and AC drives (Prentice–Hall, 1986).

[9] A. Poljugan, Speed estimator design for industrial controller based on AC wound machine, Mr.sc. Theses (in Crotian), Dept. of.El. Machines, Drives and Automation, Faculty of El. Eng. and Computing, University of Zagreb, Croatia, 2005.

[10] A. Slutej, F. Kolonić, A. Poljugan, Crane control Network, 13th International Conference on Electrical Drives and Power Electronics, (2nd Joint Croatia_Slovakia Coference), EDPE'05, September 26. – 28, 2005, CD-ROM, Dubrovnik, Croatia

[11] P.W. Lefley, W. Peasgood, R. Ong, J.K.J.Wong, Sensorless closed loop control of a slip ring induction machine using adaptive signal processing, Applied Power Electronics Conference and Exposition, APEC apos;99. Fourteenth Annual, 14-18 March, 1999.

[12] Poljugan, Alen; Kolonić, Fetah; Slutej, Alojz. DSpace Platform for Speed Estimation AC Slip-Ring Motor in Crane Mechatronic System, Proceedings (and CD-ROM) of the 11th International Power Electronics and Motion Control Conference, EPE – PEMC ’04, Riga, Latvia.

[13] C. Lascu, G. Anfreescu, Sliding-Mode Observer and Improved Integrator With DC-Offset Compensation for Flux Estimation in Sensorless-Controlled Induction Motors, IEEE Transactions on Industrial Electronics, vol. 53, no. 3, June 2006, pp. 785-794.

[14] Mihai Comanescu, Longya Xu, An Improved Flux Observer Based on PLL Frequency Estimator for sensorless Vector Control of Induction Motors, IEEE Transactions on Industrial Electronics, vol. 53, no. 1, pp. 50-56, February, 2006

[15] J.Holtz, Sensorless Control of Induction Machines-With or Without Signal Injection, IEEE Transactions on Industrial Electronics, vol. 53, no. 1, February, 2006, pp. 7-30.

[16] B. Peterson, Induction Machine Speed Estmation - Observations on Observers, Ph.D. dissertation, Dept. of Ind. El. Eng. and Automation (IEA), Lund Institute of Technology Lund, Sweden, 1996.

Fetah Kolonić (1956) received his Ph.D.E.E. in 1997, M.S.E.E. in 1990 and B.S.E.E. in 1980 at the University of Zagreb, Croatia. He is currently associate professor at the Faculty of Electrical Engineering and Computing, University of Zagreb. His major fields of study are control of electrical drives and power converters, optimal and robust control of industrial systems and integration

structure in the complex mechatronic systems. He has been author of many papers published in journals and

presented at national and international conferences. As principal investigator and project leader he has been conducting several projects funded by international and Croatian industries as well as by the Croatian government. His teaching and research include application of advanced control techniques in industrial systems.

Dr. Kolonić is a member of K¸oREMA (Croatian Society for Communication, Computing, Electronics, Measurement and Control, IEEE (Robotics and Automation Society, Industrial Electronics Society) and the Croatian section of Cigre (International Council for Large Electric Systems).

Alen Poljugan (1977) received his M.S.E.E. in 2005 and B.S.E.E. in 2001 at the University of Zagreb, Croatia. From 2001 he has been working as assistant at the Faculty of Electrical Engineering and Computing (Department of electrical machines, drives and automation). His fileds of interests are control of electrical drives and power converters, optimal and robust control of



industrial systems and integration structure in complex mechatronic systems.

He has been co-author of several papers published at national and international conferences.

Alojz Slutej (1950) received his Ph.D.E.E. in 1986, M.S.E.E. in 1981 and B.S.E.E. in 1980 at the University of Zagreb, Croatia. He is employed as Senior System Engineer and works as technical expert in ABB Crane & Harbour division in Sweden. Partly, he is engaged as associate professor at the Faculty of Electrical Engineering and Computing, University of Zagreb. His interest is mostly

in hardware and software development regarding automated container cranes activities.

He has been co-author of many papers published in journals and presented at national and international conferences.

Dr. Slutej is a member of the IFAC CCD Technical committee for distributed control systems, AISE (USA Association of Iron and Steel Engineers) and KoREMA (Croatian Society for Communications, Computing, Electronics, Measurement and Control).


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Template of Manuscripts for IREEbib.irb.hr/datoteka/425654.Clanak_ID_1666_IREE_final... · Web viewAdvanced Industrial Crane Controller Based on AC Wound Motor F. Kolonić, A. Poljugan,