Abstract—This paper presents the control strategy for varyingthe turn-on and turn-off angles of three-phase switched reluctancegenerators (SRGs) to maximize the efficiency as well as to reducethe dc-link ripple current resulting from the commutation of thephases at high speeds. The behavior of the commutation angles isanalyzed first through the offline measurement of dc-link currentand voltage, generator speed, and phase currents. The analysisof the collected data has shown that the commutation anglesproviding the minimum ripple on the dc-link current achievethe maximum generating efficiencies. A novel control technique,developed based on the finding, achieves the desired generatingset point with maximum efficiency and minimum ripple on thecharging current. The control algorithm actively searches theturn-off angles to reduce the amount of normalized ripple onthe dc-link current, which also ensures the generation with themaximum efficiency. The turn-on angle is controlled through aproportional–integral controller to generate a desired power level.The algorithm is implemented successfully on a 1-kW three-phaseSRG charging a NiMH battery pack.
THE GROWING interest in switched reluctance machines(SRMs) for automotive and industrial applications leads
to the research opportunity in precision control of the SRMs.In the process, the current energy conversion technologiesare being redesigned and reconfigured for higher performanceand efficiency. The switched reluctance generator (SRG) is anenergy conversion device that has advantages in both renewableand alternative transportation systems. With the absence ofexcitation on the rotor, the SRG provides a robust, compact,and very efficient generator system. The absence of permanentmagnets in this machine is a big cost and material availabilityadvantage over the permanent magnet machines. The nonlinear
Manuscript received October 16, 2011; revised January 21, 2012; acceptedFebruary 12, 2012. Date of publication August 1, 2012; date of current versionSeptember 14, 2012. Paper 2011-EMC-542.R1, presented at the 2011 IEEEEnergy Conversion Congress and Exposition, Phoenix, AZ, September 17–22,and approved for publication in the IEEE TRANSACTIONS ON INDUSTRY
APPLICATIONS by the Electric Machines Committee of the IEEE IndustryApplications Society.
S. Narla is with US Hybrid Corporation, Torrance, CA 90503-3807 USA(e-mail: [email protected]).
Y. Sozer is with the Department of Electrical and Computer Engineering,The University of Akron, Akron, OH 44325 USA (e-mail: [email protected]).
I. Husain is with the Department of Electrical and Computer Engineering,North Carolina State University, Raleigh, NC 27695 USA (e-mail: [email protected]).
Color versions of one or more of the figures in this paper are available onlineat http://ieeexplore.ieee.org.
Digital Object Identifier 10.1109/TIA.2012.2209850
Fig. 1. SRG system connected to the battery for charging.
Fig. 2. Phase excitation and generation period of the SRG.
behavior of the SRG poses a good challenge to the control ofthe machine. This paper addresses and mitigates the controlcomplexities so that the advantage of the SRG can be effectivelyutilized.
The experimental SRG system setup is as shown in Fig. 1.In the generating mode of operation, the phase windings of theSRG are excited for a few degrees during each electrical cycleto deliver electrical energy as shown in Fig. 2. The excitationparameters in SRG operation are the turn-on and turn-off anglesand the peak value of the phase currents [1]–[3].
The efficiency of the SRG is highly dependent on the controlstrategy implemented [3]–[5]. The control strategy is relativelydifferent at low speeds from that at high speeds [5].
For operation below the base speed, the generator phasecurrents can be controlled through a current regulator [6]. Thephase excitation begins near the stator–rotor pole alignment,and the power generation takes place over the decreasing induc-tance region during this mode of operation. Therefore, the turn-on angles should be chosen to give sufficient time for the phasecurrent to build up before entering into the torque productionregion. The hysteresis current regulators are commonly usedfor low speeds. Therefore, the dc-link current sees ripple notonly because of the phase commutation but also with the high-frequency pulse width modulation switching. At high speeds,it is difficult to regulate the current; the turn-on and turn-offangles are the only control parameters that dictate the amount ofthe generator current. The peak phase currents are dependent on
NARLA et al.: SRG CONTROLS FOR OPTIMAL POWER GENERATION AND BATTERY CHARGING 1453
the period between turn-on and turn-off angles for the excitation(conduction angle) and also their location with respect to therotor position. The ripple on the dc-link output current fromthe SRG is mostly dependent on the phase commutation athigh speeds as shown in Fig. 10. In this mode of operation,the excitation parameters are advanced such that the excitationbegins before the stator and rotor alignment position.
II. SEARCH FOR OPTIMAL CONTROLLER
Most of the existing methods have used a similar procedureto find the optimized excitation parameter controller for theirapplication which includes the following [4]–[9]:
1) sweeping the control parameters through experiment orsimulation and recording the performance data;
2) mapping of the experimental data recorded;3) developing a function or procedure based on the affecting
parameters for a desired performance measure;4) testing the controller algorithm on hardware or software
for functionality verification.
A. Existing Control Methods
In [4], a deficiency of the conventional methods that advancesthe turn-on angle proportional to the speed to achieve optimumefficiency performance is presented. An SRG model developedfrom finite element analysis was extensively simulated for vari-ous operating points with small increments of turn-on and turn-off angles; the average dc-link current, rms phase current, andshaft speed for constant dc-bus voltage have been obtained fromsimulation. At three different operating speeds, all possibleturn-on and turn-off angles are simulated to get the desiredpower output to construct a lookup table. From the mappingof the table data, it was observed that there are multiplecombinations of conduction angles providing the same dc-linkcurrent. The excitation period providing the same power withthe minimum rms phase current was chosen to be the optimumexcitation period, as minimizing the rms current also minimizesthe switching and conduction losses within the inverter. Theperformance of the developed controller was verified experi-mentally on a 6-kW SRG drive. Based on the operating speedand commanded power, the controller finds the appropriateexcitation angles from the lookup table. The proposed methodis highly dependent on the offline data collection.
In [8], a novel approach to the automatic control of excitationparameters and their characterization for easy implementationwith closed-loop control are presented. From the experimentalSRG modeling and simulation, it was observed that the optimalefficiency turn-off angles can be characterized as functions ofpower level and speed. The turn-on angle was then used to regu-late the power produced by the SRG as necessary under closed-loop control. It has been mentioned that, due to discrepanciesbetween the actual system and the machine model, it is notpossible to achieve power control under open-loop conditionsexperimentally based on a lookup table. In order to produce amap of power production for a given speed, turn-on angle, andturn-off angle, the SRG has been modeled using finite elementanalysis and simulated for four different operating speeds. The
Fig. 3. Data points collected for various turn-on and turn-off angles atdifferent average dc-link current levels.
optimum turn-on and turn-off angles were selected for a givenspeed and power level with minimum mechanical power. Theleast square curve fitting algorithm has been used based on op-timal turn-off angles over all four operating points to get curvefitted function for the turn-off angles. Experimentally, the curvefitting is based on the optimized data for four operating pointsrepresenting combinations of low and high speeds as well aslow and high power levels. The proposed method also relies onoffline data collection for finding maximum efficiency points.
B. Experimental Data Collection for Automatic AngleControl Development
Our objective is to develop an excitation control algorithmwithout relying on the offline data collection. In order tostudy the behavior of the excitation angles and relate withthe measurable quantities for high performance, we have doneextensive data collection. A wide range of turn-on and turn-offangles has been tested for analysis in an experimental setup.The parameters that were observed during the study are dc-linkaverage, ripple current, and SRG rms phase current as shownin Figs. 3–5, respectively. The mechanical input power to theSRG is calculated from the speed and torque data recorded.The output power generated by the SRG is calculated from thebattery voltage and average dc-link charging current measuredafter the bus capacitor. The turn-on angles are swept over acertain range within one electrical period, keeping the turn-offangle fixed for obtaining one set of data. For the next set ofdata, the turn-off angle is changed once and kept constant whilesweeping the possible turn-on angles at constant speed.
The data collection is performed under the followingconditions.
1) The turn-on angles are swept between −105◦ and −35◦
(electrical) in 2◦ increments.2) The turn-off angles are swept between −55◦ and −20◦
(electrical) in 3.5◦ increments.The data sets are collected for three different operating
speeds (1500, 1800, and 2000 r/min) for analysis. From theexperimentally collected data, the excitation angles for a given
1454 IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS, VOL. 48, NO. 5, SEPTEMBER/OCTOBER 2012
Fig. 4. DC-link ripple current variation for different commutation angles.
Fig. 5. SRG rms phase current variation for different commutation angles.
Fig. 6. Average dc-link current for different SRG rms phase currents.
dc-link current and operating speed are stored in a table foranalysis. Fig. 6 shows the relationship between dc-link averagecurrent and SRG rms phase current with an increase of powerlevel up to 1 kW in steps of 100 W.
All the data points collected from the experiment are plottedfor analysis. The variations of the average dc-link current, thedc-link ripple current, and the rms phase current over the widerange of turn-on and turn-off angles help to understand theSRG generating behavior. From the recorded dc-link currentdata, the optimum turn-on and turn-off angles that yield thesame power output from various combinations are identified.The identified points are joined together to form the optimizedcommutation angle curve having the minimum dc-link currentripple and the minimum rms phase current as shown in Figs. 7and 8, respectively.
The minimum rms phase current points are assumed to bethe maximum efficiency points because of the minimum copperloss [9]–[12], which is verified from Figs. 8 and 9. Core losseshave an impact on the efficiency of the operation. For that rea-son, efficiencies are measured experimentally in this research in
NARLA et al.: SRG CONTROLS FOR OPTIMAL POWER GENERATION AND BATTERY CHARGING 1455
Fig. 9. Optimal commutation angle curve chosen for maximum efficiency.
TABLE ITURN-ON AND TURN-OFF ANGLES FOR MAXIMUM EFFICIENCY
AND MINIMUM RIPPLE AT 1500 r/min
TABLE IITURN-ON AND TURN-OFF ANGLES FOR MAXIMUM EFFICIENCY
AND MINIMUM RIPPLE AT 1800 r/min
order to find the trend of the efficiency variation as a function ofthe turn-off angle. The excitation angles (in electrical degrees)that provide the maximum efficiency (η) and minimum ripple(r) in the dc-link current for different operating speeds areshown in Table I. By comparing the Figs. 7–9 and Tables I–IIIdata, it can be concluded that the excitation angles that providethe maximum efficiency also provide the minimum ripple onthe dc-link current. This finding is a key in developing thecontrol algorithm that can maximize the efficiency in realtime. Since the dc-link current ripple is a parameter that ismeasurable, the control algorithm that adjusts the excitationangles to minimize the dc-link current ripple would provide themaximum efficiency operation. With increasing dc-link currentcommand, the turn-off angle decreases to reduce the dc-linkcurrent ripple. The variations of turn-on and turn-off anglesare in the same direction for maximum efficiency possible.
TABLE IIITURN-ON AND TURN-OFF ANGLES FOR MAXIMUM EFFICIENCY
AND MINIMUM RIPPLE AT 2000 r/min
Based on the trends observed, the dc-link power output can becontrolled by the turn-on angle using a PI controller (because ofthe steady change in turn-on angle with current command), anddc-link current ripple can be controlled by turn-off angle adjust-ing control (by finding the minimum ripple operating point).
Among the data collected, the angle pairs that would givethe same charging currents are selected for comparison. Theefficiency, ripple current, and the excitation angles are all con-sidered to select the angle pairs that would give the maximumefficiency or minimum dc-link ripple currents. Two data pointsin the table do not show the similar trend with other datapoints presented in Tables I–III. For example, in Table I, for1500-r/min operating speed and 0.5-A dc-link current, althoughthe maximum efficiency turn-off angle is −30 electric degrees,the minimum ripple turn-off angle is −41 electric degrees.However, from the data collected from the experiment, the gen-erator continues to operate at maximum efficiency in generating0.5 A until the −37 electric degrees. Similarly, in Table III, for2000-r/min operating speed and 0.2-A dc-link current, althoughthe maximum efficiency turn-off angle is −41 electric degrees,the minimum ripple turn-off angle is −27 electric degrees.However, from the data collected from the experiment, thegenerator continues to operate at maximum efficiency in gen-erating 0.5 A until the −34 electric degrees. The measurementand estimation errors in the efficiency and dc ripple currentcalculations are among the factors that lead to the discrep-ancy between the turn-off angles that would give minimumripple and maximum efficiencies. In addition, the excitationangle resolution (which is 5 electrical degrees at 2000 r/minfor the 12/8 SRM) in the digital implementation contributessignificantly to the discrepancy between the turn-off anglesthat would give minimum ripple and maximum efficiencies.The excitation angles in Tables I–III are presented in electricaldegrees. The data for different turn-on and turn-off angles werecollected with 3.5 electrical degree increments.
III. CONTROLLER ALGORITHM
A. SRG Control Parameters
The controller requires two critical parameters: dc-link cur-rent ripple (Idc_ripple) and average (Idc_avg) value information,which can be obtained by using a current sensor at the dc link.The instantaneous dc-link current values from the sensor outputare measured through the analog-to-digital converter (ADC)
1456 IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS, VOL. 48, NO. 5, SEPTEMBER/OCTOBER 2012
Fig. 10. Experimental plot of dc-link battery charging current at 0.5 A/divgenerated from SRG operation with the phase currents at 2 A/div.
Fig. 11. Overall control block diagram of the turn-on and turn-off anglecontrollers.
peripheral of the Texas Instruments DSP controller. The twoparameters are computed from the instantaneous current valuesmeasured from
Idc_ripple = Imax − Imin (1)
Idc_avg =(Imax + Imin)
2(2)
Iratio =Idc_rippleIdc_avg
(3)
where Imax and Imin are the instantaneous maximum andminimum dc-link currents, respectively, as shown in Fig. 10.
B. Turn-On Angle Control
The overall control block diagram for turn-on and turn-off angles is shown in Fig. 11. For a desired dc-link averagecurrent, the actual average value is compared with the currentcommand continuously and given as an error signal to theproportional–integral (PI) controller to generate the turn-onangle. The turn-on angle controller takes effect in every twoelectrical cycles because the average value calculated from theinstantaneous dc-link current is updated every two electricalcycles. The PI controller parameters (proportional term kp = 0and integral term ki = 0.3125) are tuned such that the steady-state error is minimum with fast transient performance. In thecontroller software, the integrator sum is limited with saturationblocks to prevent the parameter overflow in the variable buffer.
Fig. 12. Step response of the average dc-link current with change in currentcommand from 0.1 to 0.5 A and from 0.5 to 0.1 A at 0.5 A/div.
Fig. 13. Transient phase current and dc-link current waveforms for change inaverage dc-link current command.
Fig. 14. Average dc-link current taking effect within two electrical cycles forcurrent command change from 0.1 to 0.5 A at 0.5 A/div.
The maximum turn-on angle constant value (i.e., θmin) is addedto the output of the PI controller to have a limiting output(when there is no input error signal to the PI). The maximumand minimum possible limits of the turn-on angle are definedwithin the saturation block for protection. The number ofinstantaneous current values read by the ADC in every 33 μsvaries with the operating speed. Therefore, there is a loss inprecision as the speed increases. This affects the values ofdc-link ripple current, dc-link average current, and the ratioof both the currents. The step response of the turn-on anglecontroller is shown in Fig. 12. The transient response of SRGphase currents and dc-link current are shown in Fig. 13. In thealgorithm, the input parameters are checked and updated forevery two electrical cycles; thus, the system bandwidth wouldbe two electrical cycles as in Fig. 14.
NARLA et al.: SRG CONTROLS FOR OPTIMAL POWER GENERATION AND BATTERY CHARGING 1457
Fig. 15. Flowchart explaining how the turn-off angle is changed effectivelybased on the ratio of dc-link ripple and average currents.
C. Turn-Off Angle Controller
The duties of the turn-on and turn-off angles are partitionedsuch that the turn-on angle is adjusted to produce the requiredpower level and the turn-off angle is tuned for that power levelto produce minimum ripple on the dc-link current. A searchingalgorithm has been developed to find the turn-off angle for min-imum ripple. The principle of the turn-off angle controller is toincrease or decrease the turn-off angle for minimum current ra-tio by comparing the latest current ratio to the previous step cur-rent ratio. This increase or decrease in turn-off angle dependson two previous steps’ turn-off angles as shown in the Fig. 15.The turn-off angle generated in the algorithm iteration is loadedinto memory for the next iteration. In each iteration, the finalturn-off angle is determined after checking the value betweenthe saturation limits. The new turn-off angle obtained will haveits effect in every two electrical cycles of phase operation.
The control algorithm uses the same excitation parametersfor all phases with appropriate shifts based on the symmet-rically displaced phase structure. The experimental results ofturn-on angle settling and the turn-off angle dynamic real-timevariation upon reaching the commanded dc-link current levelare shown in Fig. 16. The low-power observation correspondsto a lower dc-link current level (0.1 A), and the high-powerobservation corresponds to a higher dc-link current level (0.5 A)for the same dc-link voltage. The turn-on angles were adjustedappropriately to achieve maximum efficiency.
The comparison of turn-on and turn-off angle data fromoffline optimization and experiment are shown in Figs. 17and 18, respectively. The zigzag behavior happens at relativelylower power generating points where the optimal turn-off anglechanges around 5 electric degrees which is close to the reso-lution of the DSP program that could change the commutationangles.
For different dc-link set points, the closed-loop controllersettles down for a new turn-off angle. Fig. 19 shows the turn-off angles that the controller calculates and the dc-link current
Fig. 16. Turn-on and turn-off angles and average dc-link current settling withcurrent command of 0.5 A.
Fig. 17. Comparison of turn-on angles obtained from offline optimizationwith the closed-loop turn-on angle controller algorithm tested at 1800 r/min.
Fig. 18. Comparison of turn-off angles obtained from offline optimizationwith the closed-loop turn-off angle controller algorithm tested at 1800 r/min.
1458 IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS, VOL. 48, NO. 5, SEPTEMBER/OCTOBER 2012
Fig. 19. DC-link current ripple being reduced by the turn-off angle controllerwith the increase of dc-link current command.
Fig. 20. Experimental observation of maximum efficiency and minimumripple current variations for the same turn-off angles.
TABLE IVSPECIFICATIONS OF THE PROPOSED SRG EXPERIMENT
ripple that the drive produces with the increase of dc-linkaverage current command. The experimental results obtainedwith the controllers do correlate with the general trends iden-tified in Tables I–III. The results shown in Fig. 20 validatethat the optimal operating points of the commutation anglesfor achieving the maximum efficiency and minimum ripple indc-link current match closely.
IV. CONCLUSION
This paper has introduced a new controller for high-speedSRG controls to maximize the efficiency as well as to reducethe dc-link current ripple resulting from phase commutation
through the real-time control of commutation angles. Thedeveloped algorithm adjusts the excitation angles online anddoes not require offline data collection. The hardware real-time controller designed has been tested and verified with theoffline optimization data. The controller algorithm has beenimplemented in hardware using the TI 320F2812 DSP. Theexperimental observations also have proved that the optimaloperating points of commutation angles for achieving the max-imum efficiency and minimum ripple in dc-link current matchclosely (Table IV).
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[7] A. Radun, “Generating with the switched reluctance motor,” in Proc.IEEE APEC, 1994, pp. 41–47.
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Sandeep Narla received the B.E. degree in electricalengineering from Osmania University, Hyderabad,India, in 2007, and the M.S. degree in electricalengineering from The University of Akron, Akron,OH, in 2010.
He was a Teaching Assistant in the Department ofElectrical and Computer Engineering, The Univer-sity of Akron, during his Master’s program, and hisresearch was concerned with the four-quadrant con-trol of switched reluctance machines and optimumcontrol of switched reluctance generators. He was a
Graduate Intern with the National Radio Astronomy Observatory, Green Bank,WV, on system modeling and FPGA. He is currently a Project Engineer withUS Hybrid Corporation, Los Angeles, CA, where he is engaged in the designand development of solar inverters and dc–dc and dc–ac converters.
Mr. Narla is an Engineer-in-Training in the State of Michigan.
NARLA et al.: SRG CONTROLS FOR OPTIMAL POWER GENERATION AND BATTERY CHARGING 1459
Yilmaz Sozer (M’04) received the B.S. degreein electrical engineering from the Middle EastTechnical University, Ankara, Turkey, and the M.S.and Ph.D. degrees in electric power engineeringfrom Rensselaer Polytechnic Institute, Troy, NY.His graduate work focused on power electronics andthe development of control algorithms for electricmachines.
After the completion of his doctorate degree, hejoined Advanced Energy Conversion, Schenectady,NY, and developed expertise in all aspects of elec-
tronic power conversion and its control. Since August 2009, he has been withthe faculty of the Department of Electrical and Computer Engineering, The Uni-versity of Akron, Akron, OH, where he is developing a research and teachingprogram on alternative energy systems. His research interests are in the areasof control and modeling of electrical drives, alternative energy systems, designof electric machines, integrated and belt-driven starter/alternator systems, high-power isolated dc/dc converter systems, large industrial static power conversionsystems that interface energy storage, and distributed generation sources withthe electric utility.
Dr. Sozer has been involved in IEEE activities which support power elec-tronics, electric machines, and alternative energy systems. He is serving asan Associate Editor for the Electrical Machines Committee of the IEEETRANSACTIONS ON INDUSTRY APPLICATIONS and Secretary for the IEEEIndustry Applications Society Sustainable and Renewable Energy SystemsCommittee.
Iqbal Husain (S’89–M’89–SM’99–F’09) receivedthe B.Sc. degree from Bangladesh University ofEngineering and Technology, Dhaka, Bangladesh, in1987, and the M.S. and Ph.D. degrees from TexasA&M University, College Station, in 1989 and 1993,respectively.
In 1996–1997, he was a Summer Researcher withWright–Patterson Air Force Base Laboratories. Pre-viously, he taught as a Lecturer at Texas A&MUniversity and also was with Delco Chassis, Dayton,OH, as a Consulting Engineer. In 2001, he was a
Visiting Professor at Oregon State University, Corvallis. He is currently aDistinguished Professor in the Department of Electrical and Computer En-gineering, North Carolina State University, Raleigh, where he is engaged inteaching and research and is the Codirector of the Advanced TransportationEnergy Center and a Faculty Member with the NSF FREEDM EngineeringResearch Center. He was with The University of Akron, Akron, OH, prior tojoining North Carolina State University, where he built a successful electricand hybrid vehicle program. His research interests are in the areas of controland modeling of electrical drives, design of electric machines, development ofpower conditioning circuits, and design and modeling of electric and hybridvehicle systems. He has worked extensively in the development of switchedreluctance and permanent-magnet motor drives for various automotive andindustrial applications.
Dr. Husain was the recipient of the 1998 IEEE Industry Applications Society(IAS) Outstanding Young Member Award, the 2000 IEEE Third MillenniumMedal, the 2004 College of Engineering Outstanding Researcher Award, andthe 2006 SAE Vincent Bendix Automotive Electronics Engineering Award. Heis also the recipient of the 2006 IAS Magazine paper award and four IEEEIAS Committee prize paper awards. He is a Distinguished Lecturer of IAS for2012–2013.
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