HIGH PERFORMANCE CONTROLLERS BASED ON REAL PARAMETERS TO ACCOUNT FOR PARAMETER VARIATIONS DUE TO IRON SATURATION

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1 HIGH PERFORMANCE CONTROLLERS BASED ON REAL PARAMETERS TO ACCOUNT FOR PARAMETER VARIATIONS DUE TO IRON SATURATION Jorge G. Cintron-Rivera, Shanelle N. Foster, Wesley G. Zanardelli and Elias G. Strangas : Distribution Statement A. Approved for public release.

2 Report Documentation Page Form Approved OMB No Public reporting burden for the collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing the collection of information. Send comments regarding this burden estimate or any other aspect of this collection of information, including suggestions for reducing this burden, to Washington Headquarters Services, Directorate for Information Operations and Reports, 1215 Jefferson Davis Highway, Suite 1204, Arlington VA Respondents should be aware that notwithstanding any other provision of law, no person shall be subject to a penalty for failing to comply with a collection of information if it does not display a currently valid OMB control number. 1. REPORT DATE 12 AUG REPORT TYPE Briefing Charts 3. DATES COVERED to TITLE AND SUBTITLE HIGH PERFORMANCE CONTROLLERS BASED ON REAL PARAMETERS TO ACCOUNT FOR PARAMETER VARIATIONS DUE TO IRON SATURATION 6. AUTHOR(S) Jorge Cintron-Rivera; Wesley Zanardelli; Shanelle Foster; Elias Strangas 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 5d. PROJECT NUMBER 5e. TASK NUMBER 5f. WORK UNIT NUMBER 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) U.S. Army TARDEC,6501 East Eleven Mile Rd,Warren,Mi, SPONSORING/MONITORING AGENCY NAME(S) AND ADDRESS(ES) U.S. Army TARDEC, 6501 East Eleven Mile Rd, Warren, Mi, PERFORMING ORGANIZATION REPORT NUMBER # SPONSOR/MONITOR S ACRONYM(S) TARDEC 11. SPONSOR/MONITOR S REPORT NUMBER(S) # DISTRIBUTION/AVAILABILITY STATEMENT Approved for public release; distribution unlimited 13. SUPPLEMENTARY NOTES GROUND VEHICLE SYSTEMS ENGINEERING AND TECHNOLOGY SYMPOSIUM (GVSETS), SET FOR AUG , ABSTRACT Briefing Charts 15. SUBJECT TERMS 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF a. REPORT unclassified b. ABSTRACT unclassified c. THIS PAGE unclassified ABSTRACT Public Release 18. NUMBER OF PAGES 25 19a. NAME OF RESPONSIBLE PERSON Standard Form 298 (Rev. 8-98) Prescribed by ANSI Std Z39-18

3 Outline Motivation Problem Statement Experimental and FEA results comparison Proposed method Linear Approximation Methods Performance Simulation Based on experimental data. Controllers based on different parametric data Conclusion

4 Motivation There is an increasing demand for high performance motor controllers. Military ground vehicles On-board vehicle power ( kW) Electrification of vehicle loads (cooling fan, HVAC, etc...) Transportation Automotive industry Mass transportation drives, etc. Better energy generation and utilization Smart Grid Renewable energy The efficiency of a motor drive is dependent on the parameters used in the motor controller.

5 Motor Model Motor Types, (Surface PMSM and Interior PMSM) Stator Windings Rotor Magnets Shaft Surface PMSM Interior PMSM Windings are distributed in a balanced 3 phase configuration. Rotor magnets, induce a balanced 3 phase back EMF.

6 Three phase model Electrical model: i a r s L a i b i c r s r s M ac e ˆa M ab L b eˆb M bc pm pm L c e ˆc pm Back EMF voltages, e a,b,c, are produced by rotational magnetic induction.

7 Transformation into the dq axis model Using Park s transformation matrix: cos θ cos θ 2π 3 cos θ + 2π 3 P = 2 3 sin θ sin θ 2π 3 sin θ + 2π To transform from 3 phase abc to 3 equivalent axes dq0: x dq0 = P x abc Under balanced condition zero sequence quantities are nullified.

8 dq motor Model The motor model: i d v d Rs Ld e q v q i q Rs Lq e e d pm

9 Problem Statement The real situation, saturation: x i i,0 L ( i ) i x x x x x x x Lxyiy ( i, i ) L ( i ) i L i x x y x x x xy y i x i, i L ( i ) i L ( i, i ) i d d q d d d dq d q q pm i, i L ( i ) i L ( i, i ) i q d q q q q qd d q d

10 Experimental Setup Schematic diagram Controller * * id, iq Inverse Park s regulator dq PI * * abc v d, v q * v abc Inverter & gate-driver i a i b i c PMSM shaft DYNAMOMETER OR ENGINE i, i d q dq abc Park s

11 Experimental Setup with Dynamometer Dynamometer Torque Sensor PMSM Shaft Inverter/controller

12 Experimental Setup with Engine Diesel Engine Torque Sensor PMSM Generator Inverter/controller

13 Experimental Characterization Data collection: The current space vector is swept in the region of interest. s q axis I s voltage vector i V q current vector v q vd i d pm d axis Flux calculation from measured data: i, i d d q v i R i R v q q s d s d q id, iq e e

14 Characterization Results PMSM specifications: Parameters Motor Generator Rated power 125 kw 125 kw Rated speed 1500 RPM 1900 RPM Max speed 5000 RPM 3000 RPM Line voltage Max current No. poles 4 8 Test Setup: Control Room Top-Level Control Computer with LabView User Interface 125 kw PMSM i abc abc,, v abc encoder, Dyno Load CAN optical link * T and monitoring Inverter with DSP & CAN Link interface (Low-Level Controller) V dc DC Power Source Physical Barrier Experimental Room

15 L d (i d,i q ) L q (i d,i q ) Generator, Experimental Results d (i d,i q ) 125 kw PM Genertator, d-axis flux linkage Saturation due to iq q (i d,i q ) 125 kw PM Genertator, q-axis flux linkage Saturation due to id id i q x kw PM Genertator, d-axis Inductance x kw PM Genertator, q-axis Inductance Saturation due to id Saturation due to iq i d i q

16 L d (i d,i q ) L q (i d,i q ) Motor, Experimental Results 125 kw PM Motor, d-axis flux linkage 125 kw PM Motor, q-axis flux linkage 0.8 pm 1.2 d (i d,i q ) Saturation due to iq q (i d,i q ) Saturation due to id id i q x kw PM Genertator, d-axis Inductance 6 Saturation due to iq kw PM Motor, q-axis Inductance Saturation due to id i d i q

17 Inductance (H) Inductance (H) FEA parametric results Determined using a FEA magnetostatic simulation Generator Inductances Ld Lq Motor Inductances Ld Lq Current(A) Current (A) This type of simulation was used, since it is considerably less time consuming than a full transient-magnetic simulation.

18 Ld Inductance(H) Proposed Linear approximation d-axis inductance approximation: x Ld including cross-saturation id x L d including Saturation and Cross-Saturation L i i L i i sec1&1 d ( d, q ) d ( d ) d ( q ) D axis Current (A)

19 Lq Proposed Linear approximation q-axis inductance approximation: Lq, including cross-saturation Using 4 linear sectors it is possible to represent the true Lq(id,iq) iq Sector 1 and 2: Linear function with shift dependent on id. Sector 3: Linear function, where slope changes as a function of id. Sector 4: One linear function. L q 1_upper Cross-saturation 1_lower 2_upper 2_lower Sector 1 Sector 2 x 2 Cross-saturation 3_upper 3_lower x 3 Sector 3 Sector 4 Cross-saturation 4 x 4 5 i q

20 Q axis inductance (H) Proposed Linear approximation Q-axis inductance approximation sector 3: m( i ) d i x x x x 3_ lower 3_ upper 4 3_ upper id d _ rated ( 4 3) 4 3 sec.3 3_ upper 3_ lower d ( id ) id 3_ upper irated L i i m i i x i sec.3 sec.3 q ( d, q ) ( d ) ( q 3) d ( d ) 0.03 L q including Saturation and Cross-Saturation The proposed method to estimate the q-axis inductance, closely follows the experimentally determined inductance Q axis Current

21 Controller Evaluation The performance degradation due to the exclusion of the saturation effects is evaluated using a motor controller. Torque request Speed Motor Controller Based on: 1. Detailed Parameters 2. Parameters w/o cross saturation 3. Proposed Method 4. FEA based parameters i, i * * d q id pm Torque, Losses i q Motor Model Based on Experimental Data Controllers based on different parametric information were developed and evaluated in the most accurate model.

22 Power Copper Losses Power Copper Losses Power Copper Losses Power Copper Losses Results, Power Losses Losses as a function of loading Losses as a function of loading w cross-sat (LUT) w/o cross-sat (LUT) w proposed w FEA w cross-sat (LUT) w/o cross-sat (LUT) w proposed w FEA T com Generator power losses at rated speed T com Motor power losses at rated speed Losses as a function of loading Losses as a function of loading w cross-sat (LUT) w/o cross-sat (LUT) w proposed w FEA w cross-sat (LUT) w/o cross-sat (LUT) w proposed w FEA T com T com Generator power losses at 3000 RPM Motor power losses at 3000 RPM

23 Results, Torque Performance Generator Torque Performance Generator Torque Performance 320 T out w cross-sat (LUT) T out w/o cross-sat 300 T out w proposed T 280 out w FEA Motor Torque Performance Motor Torque Performance 320 T out w cross-sat (LUT) 300 T out w/o cross-sat T out w proposed 280T out w FEA T output T output T output T output T com T com At rated speed, At 3000 RPM Generator Torque performance, T com T com At rated speed, At 3000 RPM Motor Torque performance,

24 Voltage Performance Voltage commands are vital for proper operation of the motor drive. Inverters have a voltage limit and field weakening performance depends on the voltage command Voltage Commands, with a 340V Limit V mag w cross-sat (LUT) V mag w/o cross-sat V mag w proposed V mag w FEA V mag T com Motor Voltage Commands at rated Speed

25 i d commands i q commands Current Performance Motor controller, dq-axis currents commands, as a function of torque command at rated speed d-axis current commands variations, rated speed i d w cross-sat (LUT) i d w/o cross-sat i d w proposed i d w FEA T com q-axis current commands variations, rated speed T com i q w cross-sat (LUT) i q w/o cross-sat i q w proposed i q w FEA

26 Conclusions Including the saturation effects of a PMSM improves the torque performance of a motor drive system. Higher torque performance aids in reducing the motor losses. Hence, better efficiency is achieved. Increments in the torque performance increases the efficiency of the overall system. The piecewise linear approximation accurately describes the non-ideal behavior of a PMSM. This approach demonstrated a reduction in copper loss of up to 900W (efficiency gain of 1.36%) for a 125kW machine. This method is realizable in the majority of motor control DSPs due to its computational efficiency with no additional cost.