Study on Current Sensorless Vector Control Method for Electric Vehicle Drive Motor

TELKOMNIKA Indonesian Journal of Electrical Engineering
Vol.12, No.1, January 2014, pp. 254 ~ 260
DOI: http://dx.doi.org/10.11591/telkomnika.v12i1.3964  254
Received June 21, 2013; Revised August 11, 2013; Accepted September 16, 2013
Study on Current Sensorless Vector Control Method for
Electric Vehicle Drive Motor
Jing Lian, Yafu Zhou, Jing Chang, Linhui Li*, Xiaoyong Shen
School of Automotive Engineering, Dalian University of Technology, Dalian, PR China
Chuangxinyuan Highrise No.D0210, Linggong Road No.2, Ganjingzi Borough
Dalian, 116024, China; Ph./Fax:+86-411-84706475/+86-411-81907253
*Corresponding author, e-mail: 37132923@qq.com
Abstract
With the aggravation of environment pollution and the reduction of petroleum resources, the
development of electric vehicle (EV) draws more and more people’s attention. In the EV research field, that
seeking for a high efficient and reliable motor control method that suits the operating conditions and
characteristics of the vehicle drive motor has become one of the key techniques that need to be broken
through urgently. Owing to the problems that the efficient work area is narrow and it leads to over-current
phenomenon when traditional motor vector control method is applied to vehicle drive motor, this paper
presents a current sensorless vector control technique for electric vehicle drive motor. According to motor
speed and command torque which is gained from the speed loop control, this method directly controls the
magnitude and phase angle of voltage vector to realize the orientation control of the magnetic field and
then achieve the purpose of controlling the motor torque and speed. The feasibility and effectiveness of
this method are verified by simulation results and bench test. Moreover, this method can not only improve
the efficient work area, but also increase the reliability of motor control system. At the same time, it
overcomes the dependence on the current sensor, circumvents the over-current defect caused by
traditional motor vector control approach and reduces its cost. So it is a suitable and efficient control
method for electric vehicle drive motor.
Keywords: Electric vehicle, Drive motor control, Current sensorless control
Copyright © 2014 Institute of Advanced Engineering and Science. All rights reserved.
1. Introduction
With the aggravation of environment pollution and the depletion of petroleum resources,
global car industry is forced to seek new energy-saving and environmentally friendly type of
vehicle dynamic system constantly [1], which accelerates the research process of the electric
vehicle techniques [2] [3]. Motor as well as its control technique is one of the key techniques of
EV[4], which directly influences the dynamic performance, fuel economy and emission target of
the whole vehicle [5] [6]. Vector control is widely used in automotive drive motor [7], which is
controlled by regulating excitation and torque magnetic field through the PI current feedback
control [8]. Although this method succeeds in the traditional industrial control, it is difficult to
meet the demand of auto electric motor. For example, the integral action of I control component
exists IGBT(Insulated Gate Bipolar Transistor) over-current phenomenon, which will shorten the
IGBT’s life and reduce the safety and reliability of the motor controller [9] so that the ability of
dynamic system fast tracing the control target will be poor. Moreover, sole P control has
significant limitations and its control effect is unsatisfactory. Besides, the measurement error of
the current sensor is relatively obvious when small current works, which makes motor control
performance poor and inefficient [10]. And the motor will get out of control once the current
sensor goes wrong suddenly. Especially it will be very dangerous if the vehicle is in high-speed
state.
Since the stator phase voltage exerts external excitation directly to motor, so the phase
current is ultimately changed by adjusting the phase voltage for vector control, and then it
controls the Magnetic Motive Force (MMF) and space magnetic field inside the motor. So in this
paper, based on Permanent Magnet Synchronous Motor (PMSM) [11] [12], we propose a
current sensorless vector control method for electric vehicle drive motor and finds out the
optimal parameter matching of each set-point, generates three-dimensional MAP when the
motor works in different operating modes by making bench calibration of motor. When the motor

 ISSN: 2302-4046 TELKOMNIKA
TELKOMNIKA Vol. 12, No. 1, January 2014: 254 – 260
255
is under control, based on the optimal parameters in the MAP, we can refer to the three-
dimensional MAP stored in motor control program so as to obtain the optimal demand voltage
vector magnitude and phase angle, and take the space voltage vector as a control object
straightly to realize the high efficient and reliable control of the motor. This method cancels the
current loop in the vector control, breaks through the dependence on the current sensor in the
traditional vector control and reduces the cost. At the same time it avoids not only the over-
current defects caused by PI closed-loop control, but also the dependence on the current
measure. In this way, it can ensure the ability of the vehicle normal driving and improve the
reliability of the vehicle motor control system when the current sensor goes wrong suddenly
[13].
2. Drive Motor Control System
The basic idea of current sensorless vector control method for electric vehicle drive
motor proposed in this paper is to obtain command torque through the speed loop control, and
then according to motor speed and command torque, this method directly controls the
magnitude and phase angle of voltage vector to realize the orientation control of the magnetic
field and then achieve the purpose of controlling the motor torque and speed. Schematic
diagram of drive motor control system is shown in the Figure 1. It includes Motor speed and
angular position sensor, speed-loop control module, motor-control MAP query module, space
voltage vector PWM module, inverter module, power battery pack and PMSM. ( n* means
command speed, n means actual speed, Т* means torque instruction value, U* means voltage
amplitude instruction value, θ* means voltage phase instruction value, φ means rotor
mechanical angle).
*


Figure 1. Schematic diagram of drive motor control system
In order to achieve current sensorless vector control method for EV drive motor, firstly
we need to conduct the motor calibration test, forming the motor operating point control MAP
saved in the motor control program in the form of table. When the motor is under control, the
command torque values are first determined by the speed-loop control module according to the
deviation between the command speed and the actual speed. Then the voltage amplitude and
phase command are given out by motor control three-dimensional MAP query module inquiring
MAP and calculated by the surface difference according to command torque and motor speed.
Then six routes’ PWM control signals are calculated by space voltage vector PWM module
according to the amplitude and phase of the voltage as well as rotor mechanical angle, making
the inverter module generate three-phase AC voltage to control motor. The specific control
procedures of current sensorless vector control method are as follows:
2.1. The Calibration Process of Motor Control Three-dimensional MAP
Step one, in the motor bench test, select a series of operating points on the n-Т graph
of the motor, make marks every ∆n from nmin to nmax of the motor speed and every ∆T from Tmin
to Tmax of the motor torque as the calibration points of the motor control three-dimensional MAP.

ISSN: 2302-4046 
Study on Current Sensorless Vector Control Method for Electric Vehicle Drive Motor (Linhui Li)
256
Step two, at each calibration point of motor control three-dimensional MAP, adjust
voltage vector value U and phase angle θ to satisfy the demand of the motor speed n and
torque T. Select a group of U and θ that make the three-phase current Ι minimum as the optimal
value of this calibration point in the motor control three-dimensional MAP.
Step three, finish all the optimal values of calibration points in the motor control three-
dimensional MAP, construct a piece of optimal motor control three-dimensional MAP and save it
in the motor control program in the form of table.
2.2. The Process of Vector Control
Step one, motor control three-dimensional MAP query module inquires motor control
three-dimensional MAP according to target torque Т* and motor speed n*, determines the
triangular operating area of Т* and n* in the MAP and obtains the motor torque Ti, the motor
speed ni, the optimal voltage vector value Ui and the optimal phase angle value θi (i=1,2,3). As
Figure 2 shows.
Step two, the surface difference will be calculated according to Т*, n* and Ti, ni, Ui, θi
gained in the vertex of the triangle so as to get the demand optimal voltage vector U* and
optimal phase angle θ* where the motor works at the torque of Т* and the speed of n*. As is
shown in Figure 2.
Step three, according to θ* and φ*, space voltage vector PWM module gains the vector
angle θ*+φ*+π/2 where voltage vector is calculated in α-β UVW, as Figure 3 shows. Then six
routes’ PWM control signals are calculated through U* and θ*+φ*+π/2 , controlling the inverter
module to generate three-phase AC voltage to control the operation of the motor.
),,,( 1111 UTnA ),,,( 2222 UTnB
),,,( 3333 UTnC
),,,( ****
UTn

Figure 2. Triangular operating area figure of
three-dimensional MAP



U
d
q

Figure 3. Vector control coordinate system
3. Simulation Analysis
3.1. Simulation Model
This paper builds the simulation model of PMSM current sensorless control system
under the Simulink simulation environment, as is shown in Figure 4. This model mainly includes
PMSM module, MAP query module, inverter module, space voltage vector PWM module,
rotating speed and rotor angle position detection module etc. Among these, the function of the
MAP query module is to provide voltage amplitude value and phase value according to
command torque and motor speed. Space voltage vector PWM module determines voltage
amplitude and phase command as well as the rotor mechanical position according to MAP
query module, generates six routes’ PWM signals, controls the on-off of the inverter’s up or
down bridge arm, and then forms circular rotating field to control the operating of the motor.
3.2. Simulation Experiment
The parameters of the PMSM in this simulation model are: the rated speed 3000rpm,
the pole number 4, the stator phase winding resistance 2.875 Ohm, the stator d, q axis
inductance 0.85mH, permanent magnet flux 0.175Wb, moment of inertia 0.008 kg·m2
. The
parameters of the PI controller are: KP=0.55, KI=32. When the system goes into steady state
after starting with no load,if we exert TL=20N•m suddenly at the time of 0.03s, we can get the
simulation curve of the system rotating speed, torque and three-phase stator current, as is

257
shown in Figure 5 to Figure 7. It can be seen from the simulation waveform, under reference
speed 3000rpm, the system responds quickly and steady, the waveform of the phase current is
relatively ideal. When the system runs smoothly with no load, the friction torque and the motor
loss of the system can be ignored, so the mean value of the magnetic torque at this moment is
zero. At the time of 0.03s, the speed drops abruptly with suddenly load, but it can return to the
poised state rapidly. There is no offset when it runs steady.
Figure 4. Simulation model
Figure 5. Speed curve Figure 6. Torque curve
4. Test Bench
4.1. Build the Experimental Platform of the Drive Motor
In order to verify the feasibility of the current sensorless control method proposed
above for vehicle drive motor further, and study the control and calibration method of the motor
intensively, we build this experimental platform of drive motor. The experimental platform
system is shown in Figure 8, in which 1 is upper computer, 2 is motor controller which is used
for measure, 3 is power analyzer, 4 is battery pack, 5 is on-line battery charger, 6 is
dynamometer controller, 7 is eddy current dynamometer, 8 is working stand, 9 is the measured
motor, 10 is the water-cooling system, 11 is CAN communication transceiver. Based on this
experimental platform, we can perform calibration test, control method test and various
performance tests of the motor system. Figure 9 is the experimental platform to build the
physical map.
4.2. Experimental Results and Analysis
Based on the drive motor experimental platform built in the laboratory, we conduct
motor calibration experiment and efficiency experiment.

ISSN: 2302-4046 
258
4.2.1. Motor Calibration Experiment
The motor body parameters have an important impact on the control effects, but the
calculating parameter is always diverging from the actual one when the motor is designed. It is
mainly because of the fact that the material parameter is inaccurate when the motor is
designed, meanwhile, in the process of calculation, we ignore many secondary causes such as
the environment and temperature change when we conduct the test, the machining accuracy
influence and the parameter of the material property change when it used in this working
condition. So high-performance motor control must calibrate the motor in different working
conditions, and then form the motor control MAP.
Figure 7. Phase current curve Figure 8. Drive motor experiment platform
system
According to the current sensorless vector control method for EV drive motor in this
paper, select a series of working points in the motor n-T figure as the calibration points of the
motor control three-dimensional MAP. Table 1 is the experimental data calibrated at the
3072rpm, 64Nm working point of the motor. It is can be seen from the data that the motor
efficiency is different corresponding to different voltage amplitude and phase for all the working
points of the same motor, which isn’t considered in the traditional motor control method. If you
select the operating point to maximize efficiency of the voltage amplitude and phase angle of
motor control to form the motor control MAP, and then control the motor based on this MAP, you
are able to make the best use of the motor and improve the efficiency of the motor.
Table 1. Motor calibration experiment data
No. Speed/rpm Torque/Nm Voltage phase /° Voltage amplitude /V Efficiency
1 3072 64 37 230 0.89
2 3072 64 38 226 0.90
3 3072 64 40 222 0.91
4 3072 64 41 218 0.90
5 3072 64 42 214 0.89
6 3072 64 43 210 0.89
7 3072 64 44 206 0.88
4.2.2. Motor Efficiency Test
In the drive motor experimental platform, we perform the motor working efficiency test
based on the MAP formed in the calibration test. By measuring the motor input voltage and
current as well as the motor output speed and torque at each motor’s operating points in the n-T
figure, we can figure out the motor working efficiency at each operating point. The three-
dimensional surface of the motor working efficiency is shown in Figure 10.
As is shown in the figure, the motor high-efficient work area has been expanded with
the maximum efficiency reaching to 94%. It can satisfy the hybrid electrical vehicle drive motor’s
demand for maintaining high efficiency in the larger torque scope and greater speed range.

259
Figure 9. Picture of drive motor experiment
platform
Figure 10. Motor efficiency graph
5. Conclusion
In the traditional vector control method, it’s very hard for the feedback loop PI control to
satisfy the demand for the quick response, and it will cause over-current phenomenon, shorten
the IGBT’s life in motor control. Aimed at overcoming the mentioned above shortcomings, this
paper proposes a current sensorless vector control method for EV drive motor. The optimal
demand voltage vector value and phase angle are obtained by inquiring the motor control three-
dimensional MAP stored in the motor control program to conduct feed-forward vector control.
This method responds quickly, avoids over-current phenomenon, eliminates the dependence on
the current measurement, circumvents the problem of being unable to control under the
condition of current sensor’s malfunction and reduces the cost. It not only improves the control
performance, but also increases the reliability of the system at the same time.
Acknowledgment
This project is supported by the National Natural Science Foundation of China (Grant
No. 51107006, 61203171), China Postdoctoral Science Foundation (Grant No. 2012M510799,
2013T60278) and the Fundamental Research Funds for the Central Universities (Grant No.
DUT12JS03, DUT12JR04).
References
[1] Kim N, Cha SW and Peng H. Optimal Equivalent Fuel Consumption for Hybrid Electric Vehicles. IEEE
Transactions on Control System Technology. 2012; 20(3): 817-825.
[2] W Di, DC Aliprantis, K Gkritza. Electric energy and power consumption by light-duty plug-In electric
vehicles. IEEE transactions on power systems. 2011; 26(2): 738-746.
[3] Sezer V, Gokasan M and Bogosyan S. A Novel ECMS and Combined Cost Map Approach for High-
Efficiency Series Hybrid Electric Vehicles. IEEE Transactions on Control System Technology. 2011;
60(8): 3557-3570.
[4] G Ombach. Electromechanical system with IPM motor used in electric or hybrid vehicle. Compel- the
international journal for computation and mathematics in electrical and electronic engineering. 2011;
30(1): 137-150.
[5] YN Wang, XZ Zhang, XF Yuan, et al. Position-sensorless hybrid sliding-mode control of electric
vehicles with brushless DC motor. IEEE transactions on vehicular technology, 2011; 60(2): 421-432.
[6] Camus C and Farias T. The electric vehicles as a mean to reduce CO2 emissions and energy costs
in isolated regions. The Sao Miguel (Azores) case study. Energy Policy. 2012; 43: 153-165.
[7] M Njeh, S Cauet, P Coirault, et al. H-infinity control strategy of motor torque ripple in hybrid electric
vehicles: an experimental study. IET control theory and applications. 2011; 5(1): 131-144.
[8] LX Wang, YY Wang, FX Wang. Control method of permanent magnet synchronous motor used in
electric vehicle based on DSP. Electric Machines and Control. 2005; 9(1): 51-54.
[9] N Sun, YH Liang. Fuzzy PID controller design for a AC permanent magnet synchronous motor servo
system. Machinery Design & Manufacture. 2009; 11: 182-183.
[10] S Vaez-Zadeh, E Jalali. Combined vector control and direct torque control method for high

ISSN: 2302-4046 
260
performance induction motor drives. Energy Conversion and Management. 2007; 48(12): 3095-3101.
[11] Choi HH and Jung JW. Fuzzy speed control with an acceleration observer for a permanent
magnet synchronous motor. Nonlinear Dynamics. 2012; 67(2): 1717-1727.
[12] Koichi M. Development trend of the permanent magnet synchronous motor for railway traction. IEEJ
Transactions on Electrical and Electronic Engineering. 2007; 2(2): 154-161.
[13] Eiji S. Permanent magnet synchronous motor drives for hybrid electric vehicles. IEEJ Transactions on
Electrical and Electronic Engineering. 2007; 2(2): 162-168.

Study on Current Sensorless Vector Control Method for Electric Vehicle Drive Motor

More Related Content

What's hot (20)

Similar to Study on Current Sensorless Vector Control Method for Electric Vehicle Drive Motor (20)

More from Nooria Sukmaningtyas (20)

Recently uploaded (20)

Study on Current Sensorless Vector Control Method for Electric Vehicle Drive Motor