This paper presents an improved speed estimator for a permanent magnet synchronous motor (PMSM). It focuses on hybrid electric vehicles (HEVs). The speed estimator is based on reactive power model reference adaptive system (Q-MRAS). The MRAS parameters are tuned using particle swarm optimization (PSO) algorithms. The proposed method has been experimentally verified with a 100 kW, 5000 rpm PMSM, and a good agreement between the measured speed and the estimated speed is found. It is shown that the proposed method is able to handle the transition into the flux weakening mode without any problem.

References

References
1.
Tse
,
C. G.
,
Maples
,
B. A.
, and
Kreith
,
F.
,
2015
, “
The Use of Plug-In Hybrid Electric Vehicles for Peak Shaving
,”
ASME J. Energy Resour. Technol.
,
138
(
1
), p. 011201.
2.
Lulhe
,
A. M.
, and
Date
,
T. N.
,
2015
, “
A Technology Review Paper for Drives Used in Electrical Vehicle (EV) & Hybrid Electrical Vehicles (HEV)
,” International Conference on Control, Instrumentation, Communication and Computational Technologies (
ICCICCT
), Kumaracoil, India, Dec. 18–19, pp.
632
636
.
3.
M. Sabri
,
M. F.
,
Danapalasingam
,
K. A.
, and
Rahmat
,
M. F.
,
2016
, “
A Review on Hybrid Electric Vehicles Architecture and Energy Management Strategies
,”
Renew. Sustain. Energy Rev.
,
53
, pp.
1433
1442
.
4.
de Santiago
,
J.
,
Bernhoff
,
H.
,
Ekergård
,
B.
,
Eriksson
,
S.
,
Ferhatovic
,
S.
,
Waters
,
R.
, and
Leijon
,
M.
,
2012
, “
Electrical Motor Drivelines in Commercial All-Electric Vehicles: A Review
,”
IEEE Trans. Veh. Technol.
,
61
(
2
), pp.
475
484
.
5.
Wong
,
K. V.
,
2014
, “
Land-Sail Vehicle to Generate Electricity
,”
ASME J. Energy Resour. Technol.
,
137
(
1
), p. 014701.
6.
Ishikawa
,
T.
,
Seki
,
Y.
, and
Kurita
,
N.
,
2013
, “
Analysis for Fault Detection of Vector-Controlled Permanent Magnet Synchronous Motor With Permanent Magnet Defect
,”
IEEE Trans. Magn.
,
49
(
5
), pp.
2331
2334
.
7.
Verma
,
V.
,
Chakraborty
,
C.
,
Maiti
,
S.
, and
Hori
,
Y.
,
2013
, “
Speed Sensorless Vector Controlled Induction Motor Drive Using Single Current Sensor
,”
IEEE Trans. Energy Convers.
,
28
(
4
), pp.
938
950
.
8.
Aguirre
,
M.
,
Calleja
,
C.
,
Lopez-de-Heredia
,
A.
,
Poza
,
J.
,
Aranburu
,
A.
, and
Nieva
,
T.
,
2011
, “
FOC and DTC Comparison in PMSM for Railway Traction Application
,” 14th European Conference on Power Electronics and Applications (
EPE
), Birmingham, UK, Aug. 30–Sept. 1, pp.
1
10
.http://ieeexplore.ieee.org/document/6020397/
9.
Taïb
,
N.
,
Metidji
,
B.
, and
Rekioua
,
T.
,
2014
, “
A Fixed Switching Frequency Direct Torque Control Strategy for Induction Motor Drives Using Indirect Matrix Converter
,”
Arab. J. Sci. Eng.
,
39
(
3
), pp.
2001
2011
.
10.
Alonge
,
F.
,
Cirrincione
,
M.
,
D'Ippolito
,
F.
,
Pucci
,
M.
,
Sferlazza
,
A.
, and
Vitale
,
G.
,
2014
, “
Descriptor-Type Kalman Filter and TLS EXIN Speed Estimate for Sensorless Control of a Linear Induction Motor
,”
IEEE Trans. Ind. Appl.
,
50
(
6
), pp.
3754
3766
.
11.
Pereira
,
W. C. A.
,
Oliveira
,
C. M. R.
,
Santana
,
M. P.
,
Almeida
,
T. E. P.
,
Castro
,
A. G.
,
Paula
,
G. T.
, and
Aguiar
,
M. L.
,
2016
, “
Improved Sensorless Vector Control of Induction Motor Using Sliding Mode Observer
,”
IEEE Latin Am. Trans.
,
14
(
7
), pp. pp.
3110
3116
.
12.
Venkadesan
,
A.
,
Himavathi
,
S.
,
Sedhuraman
,
K.
, and
Muthuramalingam
,
A.
,
2017
, “
Design and Field Programmable Gate Array Implementation of Cascade Neural Network Based Flux Estimator for Speed Estimation in Induction Motor Drives
,”
IET Electric Power Appl.
,
11
(
1
), pp.
121
131
.
13.
Lima
,
F.
,
Kaiser
,
W.
,
da Silva
,
I. N.
, and
de Oliveira
,
A. A.
,
2012
, “
Speed Neuro-Fuzzy Estimator Applied to Sensorless Induction Motor Control
,”
IEEE Latin Am. Trans.
,
10
(
5
), pp.
2065
2073
.
14.
Panda
,
J. K.
,
Sastry
,
G. R. K.
, and
Rai
,
R. N.
,
2017
, “
A Taguchi-Fuzzy-Based Multi-Objective Optimization of a Direct Injection Diesel Engine Fueled With Different Blends of Leucas Zeylanica Methyl Ester and 2-Ethylhexyl Nitrate Diesel Additive With Diesel
,”
ASME J. Energy Resour. Technol.
,
139
(
4
), pp.
42209
42212
.
15.
Zbede
,
Y. B.
,
Gadoue
,
S. M.
, and
Atkinson
,
D. J.
,
2016
, “
Model Predictive MRAS Estimator for Sensorless Induction Motor Drives
,”
IEEE Trans. Ind. Electron.
,
63
(
6
), pp.
3511
3521
.
16.
Kumar
,
R.
,
Das
,
S.
, and
Chattopadhyay
,
A. K.
,
2016
, “
Comparative Assessment of Two Different Model Reference Adaptive System Schemes for Speed-Sensorless Control of Induction Motor Drives
,”
IET Electric Power Appl.
,
10
(
2
), pp.
141
154
.
17.
Flah
,
A.
,
Sbita
,
L.
, and
Mouna
,
B. H.
,
2011
, “
Online MRAS-PSO PMSM Parameters Estimation
,”
Int. Rev. Model. Simul.
,
4
(3), pp. 980–987.https://www.researchgate.net/publication/224764732_Online_MRAS-PSO_PMSM_parameters_estimation
18.
Gabbi
,
T. S.
,
Gründling
,
H. A.
, and
Vieira
,
R. P.
,
2016
, “
Sliding Mode MRAS Speed Observer Applied to Permanent Magnet Synchronous Motor With Decoupled Current Control
,” 42nd Annual Conference of the IEEE Industrial Electronics Society (
IECON
2016), Florence, Italy, Oct. 23–26, pp.
2929
2934
.
19.
Verma
,
V.
, and
Chakraborty
,
C.
,
2014
, “
New Series of MRAS for Speed Estimation of Vector Controlled Induction Motor Drive
,” 40th Annual Conference of the IEEE Industrial Electronics Society (
IECON
2014), Dallas, TX, Oct. 29–Nov. 1, pp.
755
761
.
20.
Marques
,
G. D.
, and
Mesquita e Sousa
,
D.
,
2011
, “
A New Sensorless MRAS Based on Active Power Calculations for Rotor Position Estimation of a DFIG
,”
Adv. Power Electron.
,
2011
, p.
970364
.
21.
Flah
,
A.
,
Novak
,
M.
,
Sbita
,
L.
, and
Novak
,
J.
,
2014
, “
Estimation of Motor Parameters for an Electrical Vehicle Application
,”
Int. J. Model. Identif. Control
,
22
(
2
), pp.
150
158
.
22.
Teja
,
A. V. R.
,
Verma
,
V.
, and
Chakraborty
,
C.
,
2015
, “
A New Formulation of Reactive-Power-Based Model Reference Adaptive System for Sensorless Induction Motor Drive
,”
IEEE Trans. Ind. Electron.
,
62
(
11
), pp.
6797
6808
.
23.
McCall
,
J.
,
2005
, “
Genetic Algorithms for Modelling and Optimisation
,”
J. Comput. Appl. Math.
,
184
(
1
), pp.
205
222
.
24.
Knowles
,
J.
, and
Corne
,
D.
,
2005
, “
Memetic Algorithms for Multiobjective Optimization: Issues, Methods and Prospects
,”
Recent Advances in Memetic Algorithms
,
W. E.
Hart
,
J. E.
Smith
, and
N.
Krasnogor
, eds.,
Springer
,
Berlin
, pp.
313
352
.
25.
Flah
,
A.
,
Kraiem
,
H.
, and
Lassaâd
,
S.
,
2015
, “
Electrical Motor Parameters Estimator Improved by a Computational Algorithm
,”
Handbook of Research on Advanced Intelligent Control Engineering and Automation
, IGI Global, Hershey, PA.
26.
Siavashi
,
M.
,
Tehrani
,
M. R.
, and
Nakhaee
,
A.
,
2016
, “
Efficient Particle Swarm Optimization of Well Placement to Enhance Oil Recovery Using a Novel Streamline-Based Objective Function
,”
ASME J. Energy Resour. Technol.
,
138
(
5
), p. 052903.
27.
Yang
,
J.
,
He
,
L.
, and
Fu
,
S.
,
2014
, “
An Improved PSO-Based Charging Strategy of Electric Vehicles in Electrical Distribution Grid
,”
Appl. Energy
,
128
, pp.
82
92
.
28.
Samanta
,
C. K.
,
Padhy
,
S. K.
,
Panigrahi
,
S. P.
, and
Panigrahi
,
B. K.
,
2013
, “
Hybrid Swarm Intelligence Methods for Energy Management in Hybrid Electric Vehicles
,”
IET Electr. Syst. Transp.
,
3
(
1
), pp.
22
29
.
29.
Kennedy
,
J.
, and
Eberhart
,
R.
,
1995
, “
Particle Swarm Optimization
,” IEEE International Conference on Neural Networks (
ICNN
), Perth, Australia, Nov. 27–Dec. 1, pp.
1942
1948
.
You do not currently have access to this content.