11 SOC 47 0 PMSM SOC PMSM 1-3 permanent magnet synchronous motor PMSM Mat- lab /SIMULINK PMSM PMSM dq T e = 3 2 pψ fi s

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1 Electri c Machines and Control Vol. 21 No. 11 Nov SOC permanent magnet synchronous motor PMSM state of charge SOC PMSM SOC DOI /j. emc TM 341 A X Energy feedback strategy of permanent magnet synchronous motor based on battery SOC LIU Xin-tianGE De-shunHE YaoZHENG Xin-xinZENG Guo-jian Clean Energy Automotive Research Institute Hefei University of Technology Hefei China Abstract Compared with the traditional mechanical braking method the energy loss could be reduced in regenerative braking of electric vehicles effectively in order to meet the speed performance of the car improve the energy efficiency and ensure the safe and reliable operation of the power battery. Motor dynamic model of electric vehicle and power battery SOC energy feedback model were established according to the analysis of braking performance and SOC. Determination of regenerative braking energy feedback optimal working point of the strategy was given and the proportion of mechanical braking and regenerative braking can get reasonable allocation in the process of braking. Finally a power system model of electric vehicle based on MATLAB was established. The simulation results show that the proposed energy feedback strategy can improve the energy recovery efficiency in the premise of the reduction performance and safety of the battery. Keywords permanent magnet synchronous motors regenerative brake energy feedback state of charge

2 11 SOC 47 0 PMSM SOC PMSM 1-3 permanent magnet synchronous motor PMSM Mat- lab /SIMULINK PMSM PMSM dq T e = 3 2 pψ fi sq + L d - L q i sd i sq 1 i 14 sd i sq dq L PMSM d L q ψ f p PMSM L d L q T e 1. 5pψ f i sq i sd i sq PMSM i sq T e % 16 - i q T b T e n PMSM T e + T b = J π dn 30 dt 2 J state of charge SOC n v n = i gi 0 v r 3 i g i 0 r 2 3

3 48 21 T e + T b = J i SOC = SOC 0-1 gi 0 dv r dt 4 C N t I dc dt 13 0 SOC 0 SOC C N dv /dt I dc I dc v 0 v v = v 0 - r T e + T b t Ji g i SOC NEDC new european driving cycle P f = 3 2 u sdi sd + u sq i sq 6 NEDC 4 1 u sd u sq dq 28 7 i sd i sq di sd u sd = R s i sd + L d - ω dt r L q i sq } NEDC di sq u sq = R s i sq + L d + ω dt r L d i sd + ω r ψ f Table 1 Parameters of the brake operating conditions of NEDC ω r n / ω r = πnp T e + T b = J dω r 9 p dt i sd 0 i sq P f P f = 3 2 R di sq si sq + L d + ω dt r ψ f i sq ~ ~ I dc 1 1 a NEDC U dc Δt T e T b ω r T e T b v 0 T e T b ω r = πpi gi r v 0 - pδt T e + T b B 1 v T e 11 J T b 1 b v B 10I dc T e I dc = 2R st e + ω U dc pψ f 3pψ r ψ f 12 f km /h m /s m /s 2 A 15 ~ ~ ~ ~ B 32 ~ ~ ~ ~ C 50 ~ ~ D 35 ~ ~ ~ ~ E 70 ~ ~ F 120 ~ ~ ~ ~ v = 10 km /h = m /s 1 c T e - T b SOC SOC 0 13 SOC 0 ~ 1 SOC 0 s

4 11 SOC 49 SOC 1 23 SOC 0 SOC 0 1 SOC 0 SOC SOC 0 Fig. 2 2 SOC T e T b Relationship between SOC and T e T b Fig. 1 1 v T e T b Relationship between v and T e T b 2 SOC SOC T e T b 2 a SOC 1 3 T e T b 2 b 2 c T e - T b T b 2. 2 v SOC 02 b 2 c SOC 0 = 0. 5 T SOC 0 = 0 SOC e - T b 0 T e T b 4 SOC 0 = 0

5 50 21 v T e - T b A v = 10 SOC = 1 x - y T e 5 13 T b + T e = 3Ji gi 0 } r 2R s T 2 e + 3pψ 2 f ω r T e = 3C Np 2 U dc ψ 2 f Δt 14 A T e = N m T b = N m SOC 0 T e 4 Fig. 4 SOC v T e - T b Projection of SOC and v in the T e - T b plane Fig. 5 5 Motor armature current waveform Fig. 3 3 T e T b Range of T e T b to meet the requirements of energy feedback 3 6 NEDC B SOC SOC SOC 7 B T e T b SOC v 2 1 Table 2 2 T e T b Parameters of T e and T b Matlab / SIMU- LINK 5 1s T e / N m T b / N m SOC v / m /s % % % % 3. 52

6 11 SOC 51 8 NEDC η Q η Q B ~ C ~ D E ~ F η Q 0. 46% 6 SOC Fig. 6 SOC and charge current curve 8 NEDC Fig. 8 Energy recovery curve of NEDC cycle 7 Fig. 7 SOC v SOC and v curves at different points 4 T e SOC % m /s Matlab /SIMULINK 1 PMSM SOC 2 3 1NIANX PENG F ZHANG H. Regenerative braking system of electric vehicle driven by brushless DC motorj. IEEE Transactions

7 52 21 on Industrial Electronics tor field-oriented control J. Transactions of China Electrotechni- 2. cal Society J GAOY CHEN L Ehsani M. Investigation of the effectiveness of SONG Shigang LI Xiaoping SUN Zechang. Analysis on the control strategy for series regenerative braking based on hybrid system theory J. Automotive Engineering LU S WESTON P HILLMANSEN S et al. Increasing the regenerative braking energy for railway vehicles J. IEEE Transactions on Intelligent Transportation Systems LU Dongbin OUYANG Minggao GU Jing et al. Optimal regenerative braking control for Permanent Magnet Synchronous Motors J in YANG Yajuan ZHAO Han ZHU Maofei. A study on the control strategy for maxinun energy recovery by regenerative braking in e- lectric vehicles J. Automotive Engineering J ZHU Hao XIE Yubing HE Jianhui. Hybrid electric bus regenerative braking parallel strategy optimization and simulation J. Journal of Central South University Science and Technology PID 6. J J WANG Xudong XIA Tao XU Xiaozhuo et al. Particle swarm PID LU Wenqi HU Yuwen JIN Hai et al. Parameter of crank press dy- space vector control of permanent magnet synchronous linear mo- namic system drived by PMSM J. Transactions of China Electrotechnical Society XU L WANG J P BAI Y et al. Adaptive robust control for driving and regenerative braking of electric vehicle J. Applied Mechanics and Materials XUG LI W XU K et al. An intelligent regenerative braking strategy for electric vehicles J. Energies SANT A V KHADKIKAR V XIAO W et al. Four-axis vector- 9. controlled dual-rotor PMSM for plug-in electric vehiclesj. J IEEE Transactions on Industrial Electronics ZHANG Changli ZHANG Yajun YAN Maode et al. Fuzzy control modeling and simulation of regenerative braking system for pure e- lectric vehicle with dual-source energy storage system J. Journal of System Simulation LU X SUN K GUERRERO J M et al. Double-quadrant state-ofcharge-based droop control method for distributed energy storage systems in autonomous DC microgridsj. IEEE Transactions on 10. Smart Grid J SONG ShixinWANG QingnianWANG Da. Control strategy for 21SUNF XIONG R. A novel dual-scale cell state-of-charge estimation approach for series-connected battery pack used in electric regenerative braking system of in-wheel motor vehicle J. Journal of Jilin University Engneering and Technology Edition J GUO Jingang WANG Junping CAO Binggang. Brake-force distribution strategy for electric vehicle based on maximum energy recovery J. Journal of Xi an Jiaotong University J CHEN Rong DENG Zhiquan YAN Yangguang. Analysis of braking process of permanent magnet synchronous motor based on ro- regenerative braking for EV and HEVC/ /Future Transportation Technology Conference &Exposition. Costa Mesa CA USA Electric and Hybrid Electric VehiclesHybrid Electric Control Systems J electric vehicles J. Proceedings of the CSEE D. 16. J LU Zhifeng LI Jun ZHOU Shiqiong et al. Control of PMSM braking energy regeneration system J. Electric Power Automation Equipment tor J. Journal of Electronic Measurement and Instrument KREINDLER L IACOB I CASARU G et al. PMSM drive using digital hall position sensors for light EV applicationsc/ / Advanced Topics in Electrical Engineering ATEE th International Symposium on. IEEE vehicles J. Journal of Power Sources LIU Hongwei HE Xiaoyin CHU Liang et al. Study on control strategy of regenerative braking for electric bus based on braking. comfort C/ / International Conference on Electronic and Mechanical Engineering and Information Technology EMEIT Vmin-EKF SOC J LIU Xintian LIU Xingtao HE yao et al. Based-Vmin-EKF SOC. estimation for power Li-ion battery packj. Control and Decision

u d = R s i d - ωl q i q u q = R s i q + ωl d i d + ωψ 1 u d u q d-q i d i q d q L d L q d q ψ f R s ω i 1 i 5th i th 5 θ 1 θ θ 3 5 5

u d = R s i d - ωl q i q u q = R s i q + ωl d i d + ωψ 1 u d u q d-q i d i q d q L d L q d q ψ f R s ω i 1 i 5th i th 5 θ 1 θ θ 3 5 5 3 5 018 10 Vol. 3 No. 5 JOURNAL OF HARBIN UNIVERSITY OF SCIENCE AND TECHNOLOGY Oct. 018 150080 Matlab /Simulink DOI 10. 15938 /j. jhust. 018. 05. 011 TM35 A 100-683 018 05-006- 06 Stator Harmonic Optimal