Dynamic Performance Simulation of Hybrid Excitation Claw-pole Alternator

Transcription

1 Intrnational Confrnc on Enrgy, Powr and Elctrical Enginring (EPEE 016) Dynamic Prformanc Simulation of Hybrid Excitation Claw-pol Altrnator Jiapng Li 1, Changqing Zhu 1,*, Min Cong and Yiming Shn 1 1 School of Elctrical Enginring, Shandong Univrsity, China Hfi Powr Supply Company, China Th mainly purpos of this papr is to analyz th dynamic prformanc of HECPA by dsigning a gntic algorithm (GA) fuzzy slf-adaptiv PI control systm for th altrnator, which is combind with th GA fuzzy control with rasoning and adaptability and th PI control with high prcision. In Sction II, th structur of th HECPA will b introducd. In addition, th mathmatical quations and global Simulink dynamic simulation modl will b prsntd. Sction III constituts a GA fuzzy slf-adaptiv PI controllr and stablishs th control ruls for th HECPA. Thn, th simulation will b carrid out in Sction IV. Finally, conclusions will b drawn in Sction V. Abstract In ordr to analyz th dynamic prformanc of hybrid xcitation claw-pol altrnator, this papr modls and simulats a GA fuzzy slf-adaptiv PI control systm for th altrnator basd on th drivd mathmatical quations. According to th simulation rsults, compard with traditional PID control systm, th dsignd systm nabls th output voltag to kp stady mor quickly and has bttr adaptiv ability. ywords-hybrid xcitation; claw-pol altrnator; dynamic prformanc; GA fuzzy control I. INTRODUCTION Th convntional lctric xcitation claw-pol altrnator (EECPA) ar widly usd bcaus of thir low cost and asy to rgulat; howvr, thy suffrd from lakag flux, noiss, high failur, low fficincy and poor output, which significantly rstrict thir furthr dvlopmnt. II. STRUCTURE AND MODEL OF THE GLOAL SYSTEM A. asic Structur Figur I shows th diagram of a brushlss HECPA introducd in this papr. Th prmannt magnt claw-pol altrnator (PMCPA) liminat th fild winding, brush and loop, and thus ar simplr and mor rliabl. Th fficincy and powr dnsity ar improvd as wll sinc xcitation is not rquird. Unfortunatly, th chang of ithr load or spd would caus th frqunt instability output voltag of PMCPA, sinc it is difficult to adjust th magnitud of th air gap magntic fild of PMCPA, which dpnds on th prmannt magnt and prmability, both th application and th dvlopmnt of PMCPA will b rstrictd in a way [1, ]. (A) SECTIONAL VIEW Hybrid xcitation claw-pol altrnator (HECPA) hav both prmannt magnt and fild winding, and th two magntizations sourcs ar concurrnt [3, 4]. Thrfor, HECPA taks th advantags of both th EECPA and PMCPA [5]. Hybrid xcitation can b utilizd to tun th magnt fild of PMCPA. y changing xcitation currnt, HECPA with givn rotating spd and load scop paramtrs can achiv stabl output voltag. Compard to traditional EECPA, HECPA has high fficincy, low spd and high powr dnsity, which maks it a vry promising tchniqu in rcnt yars. In addition, th inductancs of th HECPA ar highly nonlinar and multi variabl coupld. y using a normal PI control this nonlinar charactristic of th HECPA maks it difficult to gt satisfid prformanc such as wid dynamic rang, fast rspons and littl ovrshoot. Thus, w nd to adopt othr typs of controllrs capabl of taking into account th nonlinaritis and adaptabl to divrs conditions in ral tim [6, 7] Th authors - Publishd by Atlantis Prss () 3D FINITE-ELEMENT MODEL FIGURE I. DIAGRAM OF THE HECPA. Th introducd brushlss HECPA was proposd to ovrcom th disadvantags of th convntional EECPA and PMCPA. Th altrnator can b usd th main powr supply of th vhicl lctrical quipmnt, and it is not only to provid powr to th ignition systm and othr lctrical quipmnt, but 88

2 also to charg th battry [8, 9]. This HECPA includs stator cor, armatur windings, claw pols, xcitation brackt, DC xcitation winding and prmannt magnts. Th rotor is composd of two claws, and th two claws ar wldd togthr with magntic imprmabl matrial. On claw is fixd on th shaft and th othr on has a bor in th claw palm. Th xcitation brackt is fixd on th nd closur, and th xcitation winding wraps around th xcitation brackt, thn th xcitation winding and xcitation brackt insrt into th claw through th bor in th claw palm. Thr ar two additional air gaps btwn th brackt and th claws. Compard with th ordinary lctric xcitation claw-pol altrnator, this hybrid xcitation brushlss claw-pol altrnator rducs th xcitation loss, incrass th altrnator's powr dnsity, and improvs th altrnator's low spd powr charactristic. Furthrmor, its xcitation winding is stationary, thus th brush and slip ring can b liminatd. So it has good rliability.. Mathmatical Modl According to th Faraday s law, th inducd voltags quations can b xprssd as d A ua RAiA d u Ri d C uc RCiC whr R A, R, R C ar th stator phas winding rsistanc, i A, i, i C ar th stator phas winding currnt. Whn th flux linkags with armatur phass A,, C and fild winding f ar xprssd in trms of th inductancs and currnts as follows, L I L I L I L I f fa A f fc C ff f fpm whr R f is fild rsistanc, Ψ f is flux linkag of fild winding, and Ψ fpm is flux linkag which is gnratd by th prmannt magnts, I f is th dc xcitation currnt. Th control systm could adjust th I f, thus th HECPA obtains stabl output voltag at givn rotating spd and load. Th discussion in this papr maks th assumption that th magntic path is not saturatd and th magntic path is linar. Th matrix form of th fundamntal quations of this modl is as follows, ua LAA MA MAC ia d u M L M i A C u C MCA MC L CC i C RA 0 0 ia A 0 R 0 i 0 0 R Ci C C whr A,, C is th inducd voltag which is gnratd by both th prmannt magnt and th fild winding. C. Simulation Modl Th dynamic prformanc simulation modl is basically brokn up into four sctions: th HECPA, rctifir, GA fuzzy slf-adaptiv PI control systm and PWM gnrator. Figur II shows th global dynamic prformanc simulation modl. Th modl of th HECPA is stablishd basd on th abov mathmatical quations. L I L I L I L I A AA A A AC C Af f APM L I L I L I L I A A C C f f PM L I L I L I L I C CA A C CC C Cf f CPM whr two lik subscripts dnot a slf-inductanc, and two unlik subscripts dnot a mutual inductanc btwn th two windings. Th script L is usd to indicat that, in gnral, both th slf and mutual inductancs of th HECPA, Ψ APM, Ψ PM and Ψ CPM ar th flux linkags gnratd by th prmannt magnts. Th voltag u f inducd by th fild winding flux can b xprssd as u d R I f f f f FIGURE II. THE GLOAL DYNAMIC PERFORMANCE SIMULATION MODEL III. GA CONTROL SYSTEM A. Fuzzy Control Principl and Ruls Figur III shows th slf-inductanc of A phas windings of th introducd HECPA, which is highly nonlinar and multi variabl coupld. Fuzzy PI control has bn widly usd to control ill-dfind, nonlinar and othr systms. In this papr, 89

3 th fuzzy slf-adaptiv PI control has bn adoptd, which is combind with th fuzzy control with rasoning and adaptability and th PI control with high prcision. 8 x 10-4 LAA (H) ia (A) dgr (A) MEMERSHIP FUNCTION OF E AND EC FIGURE III. SELF-INDUCTANCE OF A PHASE WINDINGS Fuzzy control thory is put forward by Amrican profssor Zadh L A in 1973, and th basic ida of fuzzy control is to us linguistic variabls instad of a prcis mathmatical variabls, using th fuzzy rlationship instad of prcis mathmatical rlationship, using a simpl fuzzy algorithm instad of larg and complicatd calculation. Fuzzy PI control componnts four parts: fuzzification, fuzzy infrnc, fuzzy ruls bas, and dfuzzification [10]. Figur IV shows th structur of th fuzzy control systm. Th knowldg bas consists of th rul bas, oftn xprssd in th form of logical implications, such as IF THEN ruls, and th databas, containing dscriptions of th input and output variabls. Fuzzy infrnc, rlating th output actions of th controllr with th obtaind inputs according to knowldg, maks dcisions to obtain fuzzy output variabls. Givn voltag + - d/ Fuzzification Fuzzy ruls bas Fuzzy infrnc GA optimization & Dfuzzification PI controllr Hybrid xcitation Claw-pol altrnator Output FIGURE IV. STRUCTURE OF FUZZY SELF-ADAPTIVE PI CONTROL SYSTEM In ordr to mt th diffrnt tim input rquirmnts for controllr paramtrs slf-adaptiv, fuzzy controllr with rror and rror chang rat c as input, output paramtrs of PI aftr through fuzzification, fuzzy infrnc and dblurring opration, so that can mt diffrnt tim of and c on PI paramtrs slf-adaptiv rquirmnts. PI paramtrs could b modifid by th fuzzy control part on-lin. In this systm, and c ar input variabls, whr and c stand for rror and rror chang fuzzy valus [11], whos univrss of discours ar { 6, 5, 4, 3,, 1, 0, 1,, 3, 4, 5, 6} and fuzzy substs assum{n, NM, NS, ZO, PS, PM, P}, rspctivly. Th basic domain of Δkp and Δki is { 3,, 1, 0, 1,, 3}. Th symbol N stands for ngativ, P for positiv, ZO for zro, for big, M for middl, S for small. Th corrsponding mmbrship functions ar shown in Figur V. () MEMERSHIP FUNCTION OF ΔP AND ΔI FIGURE V. MEMERSHIP FUNCTION OF E, EC, ΔP AND ΔI Fuzzy ruls is th cor of a fuzzy controllr [1, 13], and its rol is to adjust PI paramtrs in ral tim, so th stablishmnt of fuzzy ruls is dirctly rlatd to th control ffct of th whol control systm. Th fuzzy rul is work out by dsignrs and nginrs of dsign xprinc and long-trm work summary. Th fuzzy control ruls of Δkp and Δki applid in this papr is shown in Tabls I and II. TALE I. FUZZY CONTROL RULES OF ΔP c N P P PM PM PS ZO ZO NM P P PM PS PS ZO NS NS PM PM PM PS ZO NS NS ZO PM PM PS ZO NS NM NM PS PS PS ZO NS NS NM NM PM PS ZO NS NM NM NM N P ZO ZO NM NM NM N N TALE II. FUZZY CONTROL RULES OF ΔI c N N N NM NM NS ZO ZO NM N N NM NS NS ZO ZO N N NM NS NS ZO PS PS ZO NM NM NS ZO PS PM PM PS NM NS ZO PS PS PM P PM ZO ZO PS PS PM PM P P ZO ZO PS PM PM P P. GA Optimization of th Fuzzy Control Systm Th fuzzy control ruls ar uncrtain bcaus of th control targt is high nonlinar. Evn if nginrs gt th fuzzy control ruls undr som crtain conditions, th ruls may b changd as th targt varying. In this study, gntic algorithm is usd to optimiz th infrnc ruls. Tabl III and Tabl IV show th fuzzy control ruls intimidatd through GA mthod. Through th optimization, 1 ruls ar liminatd and 8 ruls ar optimizd. Th output surfac of th Δkp basd on th fuzzy optimizd control ruls is shown in Figur VI. 90

4 TALE III. FUZZY CONTROL RULES OF ΔP AFTER OPTIMIZATION c N P P PM PS ZO ZO NM PM PS PS PS ZO NS NS PM PM PM PS ZO NS NS ZO PM PM PS ZO NS NM NM PS PS ZO NS NS NM PM PS ZO ZO NM NM N N P ZO NM NM N N TALE IV. FUZZY CONTROL RULES OF ΔI AFTER OPTIMIZATION c N N N NM NS ZO ZO NM NM NS NS NS ZO ZO N N NM NS NS ZO PS PS ZO NM NM NS ZO PS PM PM PS NS ZO PS PS PM PM ZO ZO ZO PS PM P P P ZO PS PM P P FIGURE VI. OUTPUT SURFACE OF THE ΔP In ordr to improv th dynamic prformanc of th xcitation control systm, th lmnts of th qury tabl nd to b adjustd according to th input variabls. To do this, this papr adjusts th cofficints (, c, up and ui ) to tuning th control systm on-lin. Th adjust function as follows 0 1, 0 1, ui ui 0 4, ui 0 4, whr (0), c(0), up(0) and ui(0) ar rfrnc valus; λ 1, λ, λ 3 and λ 4 ar tuning paramtrs; is th imum of th basic domain for th rror. Whn th cofficints ar optimizd by th gntic algorithm, adaptability function f is th crux of th mattr. Th function could b dscribd as M P t s f xp xp ' ' MP t s ss xp ' ss whr M P is th imum of ovrshoot; t s is th stting tim; ss is th stady-stat rror; M P, t s and ss ar th corrsponding xpctd valu; α, β and η ar th wight cofficint. IV. DYNAMIC PERFORMANCE SIMULATION asd on th abov dvlopd modl, th stady-stat and dynamic prformancs of a 8V HECPA ar simulatd. Th PWM gnrator s duty cycl is rgulatd by th choppr circuit. Th rsistancs and inductancs of th altrnator ar calculatd by finit-lmnt analysis. Th output voltag could b controlld to a stabl lvl by changing th xcitation currnt, though th HECPA s rotating spd may fluctuat. Figur VII shows th wavform of givn spd. Figur VIII shows th wavform of xcitation currnt. Th wavform of output voltag both undr th GA fuzzy control and traditional PID control is shown in Figur IX. c c0, c0, FIGURE VII. WAVEFORM OF GIVEN SPEED up up0 3, up0 3, 91

5 FIGURE VIII. WAVEFORM OF THE EXCITATION CURRENT inductancs of th HECPA ar highly nonlinar and multi variabl coupld. y using a normal PI control this nonlinar charactristic of th HECPA maks it difficult to gt satisfid prformanc such as wid dynamic rang, fast rspons and littl ovrshoot. Thrfor, w dsignd a GA fuzzy slfadaptiv PI control systm for th HECPA. It can b sn that by changing th xcitation currnt th fuzzy slf-adaptiv control systm can mak th output voltag quickly rachd th stady-stat 8V compard with traditional PID control. Th dynamic prformanc simulation rsults show that th HECPA with th dsignd control systm has good ability in robustnss, ral tim prformanc and stability. ACNOWLEDGMENT This work was supportd by th National Natural Scinc Foundation of China undr Projct FIGURE IX. OUTPUT VOLTAGE WAVEFORM WHEN CHANGING THE SPEED Similarly, aftr th wavform is stabl, subtract twnty prcnt load at 0.6 scond and plus twnty prcnt load whn 0.9 scond. Th wavform comparison is shown in Figur X. FIGURE X. OUTPUT VOLTAGE WAVEFORM WHEN CHANGING THE LOAD It can b sn from th rsults that th GA fuzzy slfadaptiv control systm can mak th output voltag quickly rachd th stady-stat 8V by changing th xcitation currnt. V. CONCLUSIONS In this papr, th basic structur of a brushlss HECPA has bn introducd at first. Th global simulation modl of th HECPA has bn prsntd usd th MATLA/Simulink basd on th drivd mathmatical modl of this altrnator. Th REFERENCES [1] R. Tang, Thory and Dsign of Modrn Prmannt Magnt Motors. ijing: China Machin Prss, 000. [] Y. Amara, L. Vido, M. Gabsi, E. Hoang,. A. A. Hamid, and M. Lcrivain, "Hybrid Excitation Synchronous Machins: Enrgy-Efficint Solution for Vhicls Propulsion," IEEE Transactions on Vhicular Tchnology, vol. 58, pp , 009. [3] W. Li and S. Huang, "Analysis and Dsign of Hybrid Excitation Clawpol Gnrator," Elctric Powr Componnts & Systms, vol. 39, pp , 011. [4] X. Fu and J. Zou, "Dsign and analysis of a novl hybrid xcitation synchronous gnrator," in 3rd IEEE Confrnc on Industrial Elctronics and Applications Singapor, 008, pp [5] Y. Amara, L. Vido, M. Gabsi, E. Hoang, A. Hamid n Ahmd, and M. Lcrivain, "Hybrid Excitation Synchronous Machins: Enrgy-Efficint Solution for Vhicls Propulsion," IEEE Transactions on Vhicular Tchnology, vol. 58, pp , 009. [6] L. Wang, M. Tian and Y. Gao, "Fuzzy Slf-adapting PID Control of PMSM Srvo Systm," in Elctric Machins & Drivs Confrnc, 007. IEMDC '07. IEEE Intrnational, 007, pp [7]. Tanaka and M. Sugno, "Stability analysis and dsign of fuzzy control systms," in Ntworking, Snsing and Control, 008. ICNSC 008. IEEE Intrnational Confrnc on, 008, pp [8] D. W. Qiao, X. H. Wang and C. Q. Zhu, "Study on a hybrid xcitation brushlss claw-pol altrnator with an annular PM btwn th claw pols," Dianji Yu ongzhi Xubao/lctric Machins & Control, vol. 18, pp , 014. [9] D. Qiao, X. Wang and C. Zhu, "3-D finit lmnt invstigation of flux rgulation prformanc of a novl hybrid xcitation brushlss claw-pol altrnator," in Advancd Matrials Rsarch, Jilin, China, 013, pp [10] C. Ming, S. Qiang and E. Zhou, "Nw slf-tuning fuzzy PI control of a novl doubly salint prmannt-magnt motor driv," IEEE Transactions on Industrial Elctronics, vol. 53, pp , 006. [11]. Youn and D. Sun, "Fuzzy PID Control Tchnology for Synchronous Gnrator Excitation," Intrnational Journal of Control and Automation, vol. 8, pp , [1] R. Ramya and. Slvi, "A simpl fuzzy xcitation control systm for synchronous gnrator," in Emrging Trnds in Elctrical and Computr Tchnology (ICETECT), 011 Intrnational Confrnc on, 011, pp [13] N. X. Truong, H. Wang and N. V. Ngu, "Rsarch on fuzzy PI control for switchd rluctanc wind powr invrtr with SVPWM," in Rmot Snsing, Environmnt and Transportation Enginring (RSETE), 011 Intrnational Confrnc on, 011, pp