- Email: [email protected]
Design and Implementation of a Loss Optimization Control for Electric Vehicle In-Wheel Permanent-Magnet Synchronous Motor Direct Drive System
Available online at www.sciencedirect.com
ScienceDirect Energy Procedia 105 (2017) 2253 – 2259
The 8th International Conference on Applied Energy – ICAE2016
Design and Implementation of a Loss Optimization Control for Electric Vehicle In-Wheel Permanent-Magnet Synchronous Motor Direct Drive System Qingbo Guoa, ChengMing Zhanga*, Liyi Lia, Jiangpeng Zhanga, Mingyi Wanga a
Department of Electrical Engineering Harbin Institute of Technology, No. 2 of Yikuang Street, Harbin, 150001. China
Abstract As a main driving force of electric vehicles (EVs), the loss of in-wheel permanent-magnet synchronous motor (PMSM) direct drive system can seriously affect the energy consumption of EVs. This paper proposes a loss optimization control strategy for EV in-wheel PMSM direct drive system which can optimize both the loss of PMSM and loss of inverter. The proposed method adjusts the copper loss and iron loss by optimal flux-weakening current, and as a result the PMSM achieve the lower loss in the whole operation range. According to the speed, the PWM frequency is optimized by the proposed control strategy, which can acquire high efficiency of inverter and not affect the stability of the PMSM system in the each operation condition. The optimum flux-weakening current and PWM frequency can be quickly found, and optimal effects of energy loss are verified by theoretical analysis and experimental results. © 2017 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license © 2016 The Authors. Published by Elsevier Ltd. (http://creativecommons.org/licenses/by-nc-nd/4.0/). Selection and/or peer-review under responsibility of ICAE Peer-review under responsibility of the scientific committee of the 8th International Conference on Applied Energy. Keywords: Efficiency; loss control; direct drive; double Fourier integral analysis; PMSM system.
1. Introduction With the worldwide shortage of energy, the improvement of energy efficiency and development of new energy have become a social problem. With the advantage of high energy efficiency and low emissions, the electric vehicles (EVs) are considered alternative to the traditional internal combustion engine vehicles. Compared with traditional permanent-magnet synchronous motor (PMSM) system with automated mechanical transmission (AMT) [1], the in-wheel PMSM direct drive system has the advantages of high dynamic performance and low transmission loss which is more suitable for EVs, as
* Corresponding author. Tel.: +0-086-0451-86403771; fax: +0-086-0451-86403771. E-mail address: [email protected].
1876-6102 © 2017 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer-review under responsibility of the scientific committee of the 8th International Conference on Applied Energy. doi:10.1016/j.egypro.2017.03.644
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shown in Fig.1. There are several vector control strategies for PMSM in rated speed, such as id=0 control [2], unit power factor control [3], maximum torque per ampere (MTPA) control [4] and etc. However, all these current vector control strategies only focus either the copper loss or iron loss of PMSM and ignore the inverter loss of PMSM direct drive system. This paper proposes a novel loss optimization control strategy for PMSM direct drive system which can achieve a higher efficiency compared with traditional vector control in the whole operation range. Based on the loss model of PMSM, the loss optimization control can synthetically optimize the copper loss an iron loss together. The PWM frequency is carefully adjusted to the direct drive system by the proposed control method which can decrease the loss of inverter and make the harmonic current small enough. The loss optimization control strategy can reduce the energy consumption and not affect the stability of the PMSM direct drive system for EVs. The proposed loss optimization control strategy is analyzed in both theory and experiment. 2. Loss Optimization Control Strategy 2.1. Loss Optimization of PMSM The equivalent circuits of PMSM in the d-q coordinate which rotate synchronously with an electrical angular velocity Ȧe are shown in Fig.2. The copper loss and iron loss can be calculated by the armature resistance Rs and the iron loss resistance Rc respectively. From Fig.2, the voltage equations of PMSM in the steady state are expressed as
ªU d º «U » ¬ q¼
ªid º ª 0 Rs « » « ¬ iq ¼ ¬ n pZr Lmd
n pZr Lm q º ªiod º ª 0 º » «i » «n Z \ » 0 ¼ ¬ oq ¼ ¬ p r f ¼
(1)
where Ud and Uq are the terminal voltage in d-axis and q-axis. L1d,q and Lmd,q are the armature leakageinductance and self-inductance, respectively. id and iq are the armature current, icd and icq are the exciting current in d-axis and q-axis respectively. np is the number of pole-pairs. And the current equation of PMSM in the steady state can be also described as
° ® °¯icd
iod uod Rc
id icd , ioq
n pZr Lqioq Rc , icq
iq icq
(2)
n pZr \ f Ld iod Rc
uoq Rc
From equation (1) and equation (2), the copper loss of PMSM in the steady state can be calculated as
PCu
^
2
1.5Rs (id2 iq2 ) 1.5Rs iod n pZr Lqioq Rc ª¬ioq n pZr \ f Ld iod Rc º¼
2
`
(3)
where transformation coefficient 1.5 is caused by that the current in d-axis and q-axis is calculated by the CLARKE transmission and PARK transmission in the principle of flux-value-constant.
(a)
(b)
Fig.1. PMSM drive system in EVs; PMSM with AMT; (b) PMSM direct drive system
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(a)
(b)
Fig.2. equivalent circuit of PMSM; (a) the equivalent circuit in d-axis; (b) the equivalent circuit in q-axis
As the hysteresis loss and eddy current loss of iron loss is represented by the iron loss resistance, the iron loss can also be calculated by the iron loss resistance as
PFe
2
1.5Rc (icd2 icq2 ) 1.5 n pZr Lqioq Rc 1.5 ª¬ n pZr \ f Ld iod º¼
2
Rc
(4)
The loss of PMSM can be derived from equation (3) and equation (4) as
Ploss _ PMSM
PCu PFe
f iod , ioq , Zr
(5)
The equation (5) shows that the loss of PMSM is a function of d-axis magnetizing current iod, q-axis magnetizing current ioq and angular velocity Ȧr. Based on the electromagnetic torque equation of PMSM, the q-axis magnetizing current ioq can be expressed as
ioq
2Te ª¬3n p\ f 3n p ( Lmd Lmq )iod º¼
(6)
Substituting the equation (6) into equation (5), the loss of PMSM can be described as
Ploss _ PMSM
f iod , Te , Zr
(7)
The equation (7) shows that the loss of PMSM is a function of d-axis magnetizing current iod, torque Te and speed Ȧr, and it is only an analytic function of d-axis magnetizing current in each const operation condition. Hence, there must be an optimum d-axis magnetizing current iod* which can make the loss of PMSM minimized. The optimum d-axis magnetizing current iod* can be calculated as
w Ploss _ PMSM wiod
Te const
Zr const
0
(8)
* iod iod
By applying the optimum d-axis magnetizing current iod* to the PMSM, the loss optimization control can achieve to maximum efficiency of the PMSM in the whole operation condition of EVs. 2.2. Loss Minimization of Inverter As an important part of PMSM power system, the loss of inverter can be described as
Ploss _ inverter
k1 I 02 k2 I 0 k3 I 0 f PWM
(9)
where k1, k2 and k3 are given by the characteristics of the power device. fPWM is the PWM frequency, and I0 is the effective value of phase current in the stator armature windings.
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The equation (9) shows that the loss of inverter is affected by the phase current of PMSM and the PWM frequency of power device. The phase current is determined by the equation (2) and equation (8). For decreasing the loss of inverter, the PWM frequency has to be reduced. However, there is harmonic current in the stator windings of PMSM caused by the PWM output voltage of the three-phase inverter. The lower PWM frequency will generate higher harmonic current, which could affect the reliable operation of PMSM seriously. Based on the double Fourier integral analysis, the loss optimization control proposes an analytic method to calculate the optimum PWM frequency fast and precisely. The PWM output voltage of inverter can be obtained by two time variables x(t) and y(t). The output voltage of A phase leg in the three-phase inverter can be described as
U A (t )
f ( x (t ), y (t ))
2U d c ® ¯0
y (t ) ! x (t ) y (t ) d x (t )
(10)
where x(t) is carrier signal and y(t) is fundamental (sinusoidal) signal, 2Udc is DC voltageDŽ The modulation mode of inverter in EVs is usually sinusoidal PWM (SPWM), so the fundamental component and harmonic component of output voltage are given by double Fourier integral analysis theory asˈ
U A (t ) U dc U dc M cos(Z0t T 0 )
4U dc
S
f
n f
1
¦ ¦ ®¯ m J
n
(m
m 1 n f n z0
4U dc
S
f
1
¦m J m 1
0
(m
S
S
M )sin(m ) cos[m(Zct T c )] 2 2
S ½ (11) M )sin[( m n ) ] cos[m(Zct T c ) n(Z0t T 0 )]¾ 2 2 ¿
S
where M is the modulation ratio. The DC offset of +Udc is caused by that the output voltage of inverter leg is defined with respect to the negative DC bus rather than with respect to the midpoint of the DC bus. From equation (11), the harmonic current of A phase armature windings can be obtained as
iAmn
u Amn
u
Amn
u Bmn uCmn
3 Rs jZmn Ls
(12)
where iAmn is the harmonic current in mth carrier signal and nth fundamental signal, and Ȧmn is the harmonic angular velocity in mth carrier signal and nth fundamental signal. uAmn, uBmn, uCmn are the harmonic components of three-phase voltage in mth carrier signal and nth fundamental signal, respectively. From equation (12), the loss optimization control can acquire the optimal PWM frequency fPWM* by the following,
§ f f · f ¨ i Amn ¦ i Amn ¸ i A01 ¦ ¨¨ ¦ ¸¸ m 1 n f n 2 ( m 0) © n z0 ¹
THDmax f PWM
* f PWM
where THDmax is maximum THD in each operation condition of EVs for keeping the system stable.
(13)
Qingbo Guo et al. / Energy Procedia 105 (2017) 2253 – 2259 * f PWM
id*
Tref
ud*
id iq
Ze
uĮ* DE
uq*
iq*
dq
* uabc
uȕ*
isĮ isȕ
abc
DE
ia ib ic
Te
d dt
Fig.3. proposed PMSM direct drive system
Fig.4. Experimental platform
By adjusting the flux-weakening current iod to the optimum iod* and PWM frequency fPWM to the optimal frequency fPWM*, the loss optimization control can make PMSM direct drive system approach maximum efficiency in the whole operation range of EVs and not affect the stability of system. 3. Experiment Study To compare the efficiency between proposed control strategy and traditional control strategy, the proposed PMSM direct drive system is designed and implemented as shown in Fig.3. Based on the speed and torque from the throttle, the loss optimization controller optimizes both the stator current and PWM frequency, by which the PMSM system will achieve minimum energy loss in the whole range of EVs. The Fig.4 shows the experimental platform for electric vehicle in-wheel PMSM direct drive system. The special dynamometer for EV/HEV drives the PMSM and serves as the mechanical load to simulate the operation condition in EV. The model parameters of the PMSM are listed in Table I. Table 1. Model parameters of PMSM Parameter
Value
Rate power
30kW
Rate speed
360rpm
Poles
22
Slots
24
Phase resistance
0.06ȍ
Phase inductance
3.18mH
Flux linkage
0.623Wb
DC link range
360-420V
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Qingbo Guo et al. / Energy Procedia 105 (2017) 2253 – 2259 350
0.9
350
0.25
300
0.8
300
0.2
250
0.7
250
0.6
200
0.5
150
0.4 100
Speed [rpm]
Speed [rpm]
2258
0.15 200 150
0.1
100
0.05
0.3 50
50
0.2 100
200
300 400 500 Torque [N·m]
600
700
Fig.5. Efficiency of PMSM in loss optimization control
0 100
200
300 400 500 Torque [N·m]
600
700
Fig.6. Difference of optimization control and id=0 control
The experiment results of the PMSM direct drive system are displayed in Fig.5. Although the efficiency of PMSM system in traditonal id=0 control has reached 90%, the proposed loss optimization control strategy can still broaden the high efficiency area of PMSM direct drive system. Fig.6 shows the difference between system efficiency of loss optimization control and traditional id=0 control. The efficiency in the loss optimization control is higher than the efficiency in id=0 control in the each operation condition of EVs and the system can acquire a higher efficiency optimization effect at low speed where the PWM frequency can be reduced more. The experimental results show that, compared with traditional control strategy, the loss optimization control can make in-wheel PMSM direct drive system achieve the lower energy consumption in the whole operation range of EVs. 4. Conclusion This paper designs a novel loss optimization control strategy for EV in-wheel PMSM direct drive system which takes consideration on both loss of PMSM and loss of inverter. The flux-weakening current is optimally controlled according to the operating speed and the load conditions to optimize the copper loss and iron loss together, and as a result the efficiency of PMSM is increased in the whole operation range of EVs. The proposed control method can adjust the PWM frequency to the optimal value for operating speed, which could achieve the lower loss of inverter and not affect the stability of the PMSM system in each operation condition of EVs. Both theoretical analysis and experimental results prove that loss optimization control could minimize the energy loss of in-wheel PMSM direct drive system without decreasing the stability of system in the whole operation range of EVs. Acknowledgements This work was supported in part by the National Science Fund for Distinguished Young Scholars (No.51225702) and in part by the State Key Program of National Natural Science Foundation of China (No.51537002) and in part by the National key S&T Special Projects of China (No.2012ZX045001051). References [1] Liang Lia, Xujian Lia, Xiangyu Wanga, Jian Songa, Kai Hea, Chenfeng Lia. Analysis of downshift’s improvement to energy efficiency of an electric vehicle during regenerative braking. Applied Energy. 2015;176:125–137. [2] A. Arroyo, M. Manana, C. Gomez, I. Fernandez, F. Delgado, Ahmed F. Zobaa. A methodology for the low-cost optimisation of small wind turbine performance. Applied Energy. 2012;104:1-9. [3] Jemaa Brahmi , Lotfi Krichen, Abderrazak Ouali. A comparative study between three sensorless control strategies for PMSG in wind energy conversion system. Applied Energy. 2009;86:1565–1573. [4] S.-Y. Jung, J. Hong, K. Nam. Current minimizing torque controlof the IPMSM using Ferrari’s method. IEEE Trans. Power Electron. 2013;28:5603–5617.
Qingbo Guo et al. / Energy Procedia 105 (2017) 2253 – 2259
Biography Chengming Zhang received the B.E., M.E., and D.E. degrees from the Harbin Institute of Technology (HIT), China, in 2005, 2007, and 2013, respectively. Since 2013, He has been a lecturer with the School of Electrical Engineering and Automation, HIT. His research areas include high efficiency motor systems, energy conversion and control.
2259
ScienceDirect Energy Procedia 105 (2017) 2253 – 2259
The 8th International Conference on Applied Energy – ICAE2016
Design and Implementation of a Loss Optimization Control for Electric Vehicle In-Wheel Permanent-Magnet Synchronous Motor Direct Drive System Qingbo Guoa, ChengMing Zhanga*, Liyi Lia, Jiangpeng Zhanga, Mingyi Wanga a
Department of Electrical Engineering Harbin Institute of Technology, No. 2 of Yikuang Street, Harbin, 150001. China
Abstract As a main driving force of electric vehicles (EVs), the loss of in-wheel permanent-magnet synchronous motor (PMSM) direct drive system can seriously affect the energy consumption of EVs. This paper proposes a loss optimization control strategy for EV in-wheel PMSM direct drive system which can optimize both the loss of PMSM and loss of inverter. The proposed method adjusts the copper loss and iron loss by optimal flux-weakening current, and as a result the PMSM achieve the lower loss in the whole operation range. According to the speed, the PWM frequency is optimized by the proposed control strategy, which can acquire high efficiency of inverter and not affect the stability of the PMSM system in the each operation condition. The optimum flux-weakening current and PWM frequency can be quickly found, and optimal effects of energy loss are verified by theoretical analysis and experimental results. © 2017 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license © 2016 The Authors. Published by Elsevier Ltd. (http://creativecommons.org/licenses/by-nc-nd/4.0/). Selection and/or peer-review under responsibility of ICAE Peer-review under responsibility of the scientific committee of the 8th International Conference on Applied Energy. Keywords: Efficiency; loss control; direct drive; double Fourier integral analysis; PMSM system.
1. Introduction With the worldwide shortage of energy, the improvement of energy efficiency and development of new energy have become a social problem. With the advantage of high energy efficiency and low emissions, the electric vehicles (EVs) are considered alternative to the traditional internal combustion engine vehicles. Compared with traditional permanent-magnet synchronous motor (PMSM) system with automated mechanical transmission (AMT) [1], the in-wheel PMSM direct drive system has the advantages of high dynamic performance and low transmission loss which is more suitable for EVs, as
* Corresponding author. Tel.: +0-086-0451-86403771; fax: +0-086-0451-86403771. E-mail address: [email protected].
1876-6102 © 2017 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer-review under responsibility of the scientific committee of the 8th International Conference on Applied Energy. doi:10.1016/j.egypro.2017.03.644
2254
Qingbo Guo et al. / Energy Procedia 105 (2017) 2253 – 2259
shown in Fig.1. There are several vector control strategies for PMSM in rated speed, such as id=0 control [2], unit power factor control [3], maximum torque per ampere (MTPA) control [4] and etc. However, all these current vector control strategies only focus either the copper loss or iron loss of PMSM and ignore the inverter loss of PMSM direct drive system. This paper proposes a novel loss optimization control strategy for PMSM direct drive system which can achieve a higher efficiency compared with traditional vector control in the whole operation range. Based on the loss model of PMSM, the loss optimization control can synthetically optimize the copper loss an iron loss together. The PWM frequency is carefully adjusted to the direct drive system by the proposed control method which can decrease the loss of inverter and make the harmonic current small enough. The loss optimization control strategy can reduce the energy consumption and not affect the stability of the PMSM direct drive system for EVs. The proposed loss optimization control strategy is analyzed in both theory and experiment. 2. Loss Optimization Control Strategy 2.1. Loss Optimization of PMSM The equivalent circuits of PMSM in the d-q coordinate which rotate synchronously with an electrical angular velocity Ȧe are shown in Fig.2. The copper loss and iron loss can be calculated by the armature resistance Rs and the iron loss resistance Rc respectively. From Fig.2, the voltage equations of PMSM in the steady state are expressed as
ªU d º «U » ¬ q¼
ªid º ª 0 Rs « » « ¬ iq ¼ ¬ n pZr Lmd
n pZr Lm q º ªiod º ª 0 º » «i » «n Z \ » 0 ¼ ¬ oq ¼ ¬ p r f ¼
(1)
where Ud and Uq are the terminal voltage in d-axis and q-axis. L1d,q and Lmd,q are the armature leakageinductance and self-inductance, respectively. id and iq are the armature current, icd and icq are the exciting current in d-axis and q-axis respectively. np is the number of pole-pairs. And the current equation of PMSM in the steady state can be also described as
° ® °¯icd
iod uod Rc
id icd , ioq
n pZr Lqioq Rc , icq
iq icq
(2)
n pZr \ f Ld iod Rc
uoq Rc
From equation (1) and equation (2), the copper loss of PMSM in the steady state can be calculated as
PCu
^
2
1.5Rs (id2 iq2 ) 1.5Rs iod n pZr Lqioq Rc ª¬ioq n pZr \ f Ld iod Rc º¼
2
`
(3)
where transformation coefficient 1.5 is caused by that the current in d-axis and q-axis is calculated by the CLARKE transmission and PARK transmission in the principle of flux-value-constant.
(a)
(b)
Fig.1. PMSM drive system in EVs; PMSM with AMT; (b) PMSM direct drive system
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Qingbo Guo et al. / Energy Procedia 105 (2017) 2253 – 2259
(a)
(b)
Fig.2. equivalent circuit of PMSM; (a) the equivalent circuit in d-axis; (b) the equivalent circuit in q-axis
As the hysteresis loss and eddy current loss of iron loss is represented by the iron loss resistance, the iron loss can also be calculated by the iron loss resistance as
PFe
2
1.5Rc (icd2 icq2 ) 1.5 n pZr Lqioq Rc 1.5 ª¬ n pZr \ f Ld iod º¼
2
Rc
(4)
The loss of PMSM can be derived from equation (3) and equation (4) as
Ploss _ PMSM
PCu PFe
f iod , ioq , Zr
(5)
The equation (5) shows that the loss of PMSM is a function of d-axis magnetizing current iod, q-axis magnetizing current ioq and angular velocity Ȧr. Based on the electromagnetic torque equation of PMSM, the q-axis magnetizing current ioq can be expressed as
ioq
2Te ª¬3n p\ f 3n p ( Lmd Lmq )iod º¼
(6)
Substituting the equation (6) into equation (5), the loss of PMSM can be described as
Ploss _ PMSM
f iod , Te , Zr
(7)
The equation (7) shows that the loss of PMSM is a function of d-axis magnetizing current iod, torque Te and speed Ȧr, and it is only an analytic function of d-axis magnetizing current in each const operation condition. Hence, there must be an optimum d-axis magnetizing current iod* which can make the loss of PMSM minimized. The optimum d-axis magnetizing current iod* can be calculated as
w Ploss _ PMSM wiod
Te const
Zr const
0
(8)
* iod iod
By applying the optimum d-axis magnetizing current iod* to the PMSM, the loss optimization control can achieve to maximum efficiency of the PMSM in the whole operation condition of EVs. 2.2. Loss Minimization of Inverter As an important part of PMSM power system, the loss of inverter can be described as
Ploss _ inverter
k1 I 02 k2 I 0 k3 I 0 f PWM
(9)
where k1, k2 and k3 are given by the characteristics of the power device. fPWM is the PWM frequency, and I0 is the effective value of phase current in the stator armature windings.
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The equation (9) shows that the loss of inverter is affected by the phase current of PMSM and the PWM frequency of power device. The phase current is determined by the equation (2) and equation (8). For decreasing the loss of inverter, the PWM frequency has to be reduced. However, there is harmonic current in the stator windings of PMSM caused by the PWM output voltage of the three-phase inverter. The lower PWM frequency will generate higher harmonic current, which could affect the reliable operation of PMSM seriously. Based on the double Fourier integral analysis, the loss optimization control proposes an analytic method to calculate the optimum PWM frequency fast and precisely. The PWM output voltage of inverter can be obtained by two time variables x(t) and y(t). The output voltage of A phase leg in the three-phase inverter can be described as
U A (t )
f ( x (t ), y (t ))
2U d c ® ¯0
y (t ) ! x (t ) y (t ) d x (t )
(10)
where x(t) is carrier signal and y(t) is fundamental (sinusoidal) signal, 2Udc is DC voltageDŽ The modulation mode of inverter in EVs is usually sinusoidal PWM (SPWM), so the fundamental component and harmonic component of output voltage are given by double Fourier integral analysis theory asˈ
U A (t ) U dc U dc M cos(Z0t T 0 )
4U dc
S
f
n f
1
¦ ¦ ®¯ m J
n
(m
m 1 n f n z0
4U dc
S
f
1
¦m J m 1
0
(m
S
S
M )sin(m ) cos[m(Zct T c )] 2 2
S ½ (11) M )sin[( m n ) ] cos[m(Zct T c ) n(Z0t T 0 )]¾ 2 2 ¿
S
where M is the modulation ratio. The DC offset of +Udc is caused by that the output voltage of inverter leg is defined with respect to the negative DC bus rather than with respect to the midpoint of the DC bus. From equation (11), the harmonic current of A phase armature windings can be obtained as
iAmn
u Amn
u
Amn
u Bmn uCmn
3 Rs jZmn Ls
(12)
where iAmn is the harmonic current in mth carrier signal and nth fundamental signal, and Ȧmn is the harmonic angular velocity in mth carrier signal and nth fundamental signal. uAmn, uBmn, uCmn are the harmonic components of three-phase voltage in mth carrier signal and nth fundamental signal, respectively. From equation (12), the loss optimization control can acquire the optimal PWM frequency fPWM* by the following,
§ f f · f ¨ i Amn ¦ i Amn ¸ i A01 ¦ ¨¨ ¦ ¸¸ m 1 n f n 2 ( m 0) © n z0 ¹
THDmax f PWM
* f PWM
where THDmax is maximum THD in each operation condition of EVs for keeping the system stable.
(13)
Qingbo Guo et al. / Energy Procedia 105 (2017) 2253 – 2259 * f PWM
id*
Tref
ud*
id iq
Ze
uĮ* DE
uq*
iq*
dq
* uabc
uȕ*
isĮ isȕ
abc
DE
ia ib ic
Te
d dt
Fig.3. proposed PMSM direct drive system
Fig.4. Experimental platform
By adjusting the flux-weakening current iod to the optimum iod* and PWM frequency fPWM to the optimal frequency fPWM*, the loss optimization control can make PMSM direct drive system approach maximum efficiency in the whole operation range of EVs and not affect the stability of system. 3. Experiment Study To compare the efficiency between proposed control strategy and traditional control strategy, the proposed PMSM direct drive system is designed and implemented as shown in Fig.3. Based on the speed and torque from the throttle, the loss optimization controller optimizes both the stator current and PWM frequency, by which the PMSM system will achieve minimum energy loss in the whole range of EVs. The Fig.4 shows the experimental platform for electric vehicle in-wheel PMSM direct drive system. The special dynamometer for EV/HEV drives the PMSM and serves as the mechanical load to simulate the operation condition in EV. The model parameters of the PMSM are listed in Table I. Table 1. Model parameters of PMSM Parameter
Value
Rate power
30kW
Rate speed
360rpm
Poles
22
Slots
24
Phase resistance
0.06ȍ
Phase inductance
3.18mH
Flux linkage
0.623Wb
DC link range
360-420V
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Qingbo Guo et al. / Energy Procedia 105 (2017) 2253 – 2259 350
0.9
350
0.25
300
0.8
300
0.2
250
0.7
250
0.6
200
0.5
150
0.4 100
Speed [rpm]
Speed [rpm]
2258
0.15 200 150
0.1
100
0.05
0.3 50
50
0.2 100
200
300 400 500 Torque [N·m]
600
700
Fig.5. Efficiency of PMSM in loss optimization control
0 100
200
300 400 500 Torque [N·m]
600
700
Fig.6. Difference of optimization control and id=0 control
The experiment results of the PMSM direct drive system are displayed in Fig.5. Although the efficiency of PMSM system in traditonal id=0 control has reached 90%, the proposed loss optimization control strategy can still broaden the high efficiency area of PMSM direct drive system. Fig.6 shows the difference between system efficiency of loss optimization control and traditional id=0 control. The efficiency in the loss optimization control is higher than the efficiency in id=0 control in the each operation condition of EVs and the system can acquire a higher efficiency optimization effect at low speed where the PWM frequency can be reduced more. The experimental results show that, compared with traditional control strategy, the loss optimization control can make in-wheel PMSM direct drive system achieve the lower energy consumption in the whole operation range of EVs. 4. Conclusion This paper designs a novel loss optimization control strategy for EV in-wheel PMSM direct drive system which takes consideration on both loss of PMSM and loss of inverter. The flux-weakening current is optimally controlled according to the operating speed and the load conditions to optimize the copper loss and iron loss together, and as a result the efficiency of PMSM is increased in the whole operation range of EVs. The proposed control method can adjust the PWM frequency to the optimal value for operating speed, which could achieve the lower loss of inverter and not affect the stability of the PMSM system in each operation condition of EVs. Both theoretical analysis and experimental results prove that loss optimization control could minimize the energy loss of in-wheel PMSM direct drive system without decreasing the stability of system in the whole operation range of EVs. Acknowledgements This work was supported in part by the National Science Fund for Distinguished Young Scholars (No.51225702) and in part by the State Key Program of National Natural Science Foundation of China (No.51537002) and in part by the National key S&T Special Projects of China (No.2012ZX045001051). References [1] Liang Lia, Xujian Lia, Xiangyu Wanga, Jian Songa, Kai Hea, Chenfeng Lia. Analysis of downshift’s improvement to energy efficiency of an electric vehicle during regenerative braking. Applied Energy. 2015;176:125–137. [2] A. Arroyo, M. Manana, C. Gomez, I. Fernandez, F. Delgado, Ahmed F. Zobaa. A methodology for the low-cost optimisation of small wind turbine performance. Applied Energy. 2012;104:1-9. [3] Jemaa Brahmi , Lotfi Krichen, Abderrazak Ouali. A comparative study between three sensorless control strategies for PMSG in wind energy conversion system. Applied Energy. 2009;86:1565–1573. [4] S.-Y. Jung, J. Hong, K. Nam. Current minimizing torque controlof the IPMSM using Ferrari’s method. IEEE Trans. Power Electron. 2013;28:5603–5617.
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Biography Chengming Zhang received the B.E., M.E., and D.E. degrees from the Harbin Institute of Technology (HIT), China, in 2005, 2007, and 2013, respectively. Since 2013, He has been a lecturer with the School of Electrical Engineering and Automation, HIT. His research areas include high efficiency motor systems, energy conversion and control.
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