Wheel slip control in high-speed trains is used to reduce the acceleration time and produce the maximum traction motor power. For controlling slip in a complete model of a train consisting of the traction motors, it is needed to keep the adhesion coefficient as much as possible by controlling the input voltage. In this article, integrated sliding mode and direct torque controls are used to control the transient traction in a full model of a high-speed railcar consisting of a wagon, two bogies, four wheelsets, and four traction motors. Cosimulations in SIMPACK with MATLAB/Simulink are carried out to evaluate the performance of the designed control structure. By comparing the results of the open-loop and closed-loop simulations, it is shown the acceleration time of the high-speed railcar is decreased 26% and the production of the traction motor power is increased 32% for both dry and wet surface conditions. It is also shown that the designed control structure is stable and robust in the presence of uncertainties.
AguirreMCallejaCLopez-de-HerediaA, et al. (2011) FOC and DTC comparison in PMSM for railway traction application. In: Proceedings of the 2011 14th European conference on power electronics and applications, Birmingham, UK, 30 August–1 September 2011, pp. 1–10. IEEE.
2.
AldairAWangW (2012) A neurofuzzy controller for full vehicle active suspension systems. Journal of Vibration and Control18(12): 1837–1854.
3.
AraratÖSöylemezMT (2018) Event-based slip-slide control system for railway vehicles. Journal of Vibration and Control24(10): 1987–2000.
4.
BandyopadhyayBDeepakFKimK-S (2009) Sliding Mode Control Using Novel Sliding Surfaces. Berlin Heidelberg: Springer.
5.
BlaschkeF (1971) A new method for the structural decoupling of AC induction machines. In: Conference record IFAC, Duesseldorf, Germany, October 1971, pp. 1–15.
6.
CaiW-CLiD-YSongY-D (2015) A novel approach for active adhesion control of high-speed trains under antiskid constraints. IEEE Transactions on Intelligent Transportation Systems16(6): 3213–3222.
7.
CasadeiDProfumoFSerraG, et al. (2002) FOC and DTC: two viable schemes for induction motors torque control. IEEE transactions on Power Electronics17(5): 779–787.
8.
TaniYDongHLuJ, et al. (2016) A super-twisting-like algorithm and its application to train operation control with optimal utilization of adhesion force. IEEE Transactions on Intelligent Transportation Systems17(11): 3035–3044.
9.
CheokADShiomiS (1998) A fuzzy logic based anti-skid control system for railway applications. In: Proceedings KES'98. 1998 second international conference on knowledge-based intelligent electronic systems, Adelaide, SA, Australia, 21–23 April 1998, pp. 195–201. IEEE.
10.
CheokADShiomiS (2000) Combined heuristic knowledge and limited measurement based fuzzy logic antiskid control for railway applications. IEEE Transactions on Systems, Man and Cybernetics, Part C (Applications and Reviews)30(4): 557–568.
11.
CruzCGallegosMAlvarezR, et al. (2004) Comparison of several nonlinear controllers for induction motors. In: 9th IEEE international power electronics congress, 2004. CIEP 2004, Celaya, Guanajuato, Mexico, 17–22 October 2004, pp. 134–139. IEEE.
12.
DincelENakHAkkayaŞ, et al. (2018) Robust control of railway traction system. IFAC-PapersOnLine51(25): 171–177.
13.
ElmadanyMMAl-MajedMI (2001) Quadratic synthesis of active controls for a quarter-car model. Journal of Vibration and Control7(8): 1237–1252.
FanZKorenYWeheD (1995) A simple traction control for tracked vehicles. In: American control conference proceedings of the 1995, Seattle, WA, USA, 21–23 June 1995, pp. 1176–1177. IEEE, .
16.
FrylmarkDJohnssonS (2003) Automatic slip control for railway vehicles. Msc Thesis, Institutionen för Systemteknik, Linköping, Sweden.
17.
HuHLiY (2002) Applications of induction motor drive based on DTC in railway traction. In: Proceedings. International conference on power system technology, Kunming, China, 13–17 October 2002, pp. 2285–2289. IEEE.
18.
HuLQinJYangZ, et al. (2014) A novel real-time traction force reference distribution adhesion control for high-speed train. In: 2014, civil-comp press, Stirlingshire, UK.
19.
HuangZXuZChenB, et al. (2017) Sliding mode control for urban railway anti-slip system based on optimal slip ratio estimation with forgetting factor recursive least-squares. 2017 36th Chinese control conference (CCC), Dalian, China, 26–28 July 2017, pp. 9502–9507. IEEE.
20.
HouHYuXXuL, et al. (2019) Discrete-time terminal sliding-mode tracking control with alleviated chattering. IEEE/ASME Transactions on Mechatronics24(4): 1808–1817.
21.
InaridaSKojimaTShimadaM, et al. (2001) Train traction systems for passenger comfort and easier maintenance. Hitachi review50(4): 134–138.
22.
IshikawaYKawamuraA (1997) Maximum adhesive force control in super high speed train. 1997, Proceedings of the power conversion conference, Nagaoka, Japan, 6–6 August 1997, pp. 951–954. IEEE.
23.
IshratTLedwichGVilathgamuwaM, et al. (2016) Wheel slip control based on traction force estimaton of electric locomotives. Power engineering conference (AUPEC), 2016 Australasian universities, Brisbane, QLD, Australia, 25–28 September 2016, pp. 1–6. IEEE.
24.
KadowakiSOhishiKYasukawaS, et al. (2004) Anti-skid re-adhesion control based on disturbance observer considering air brake for electric commuter train. AMC'04. The 8th IEEE international workshop on advanced motion control, Kawasaki, Japan, 28–28 March 2004, pp. 607–612. IEEE.
25.
KnotheK (2008) History of wheel/rail contact mechanics: From Redtenbacher to Kalker. Vehicle system dynamics46(1–2): 9–26.
26.
LangWRothG (1993) Optimale Kraftschlussausnutzung bei Hochleistung-Schienenfahrzeugen. ETR. Eisenbahntechnische Rundschau42(1–2): 61–66.
27.
LeeH (2019) A comparison of longitudinal adhesion models and identification of the dominant adhesion parameter. Vehicle system dynamics. 58(2020): 1–14.
28.
LeeHUtkinVI (2007) Chattering suppression methods in sliding mode control systems. Annual reviews in control31(2): 179–188.
29.
Le-HuyH (1999) Comparison of field-oriented control and direct torque control for induction motor drives. Conference record of the 1999 IEEE industry applications conference. Thirty-Forth IAS annual meeting (Cat. No. 99CH36370), Phoenix, AZ, USA, 3–7 October 1999, pp. 1245–1252. IEEE.
LiXDongH-Y (2012) Modeling of high-speed traction motors control system based on train communication network. Information Technology Journal11(4): 436–440.
33.
LyuYBergsethEOlofssonU, et al. (2015) On the relationships among wheel-rail surface topography, interface noise and tribological transitions. Wear338–339: 36–46.
34.
MahajanPGargRGuptaN, et al. (2014) Design and simulation of H-bridge fed direct torque controlled electric traction drive. 2014 IEEE 6th India international conference on power electronics (IICPE), Kurukshetra, India, 8–10 December 2014, pp. 1–6. IEEE.
35.
MaoZYanX-GJiangB, et al. (2019) Adaptive fault-tolerant sliding-mode control for high-speed trains with actuator faults and uncertainties. IEEE Transactions on Intelligent Transportation Systems21(16): 1–12.
36.
MatsumotoYEguchiNKawamuraA (2001) Novel re-adhesion control for train traction system of the “Shinkansen” with the estimation of wheel-to-rail adhesive force. In: Industrial electronics society, 2001. IECON'01. The 27th annual conference of the IEEE, Denver, CO, USA, 29 November–2 December 2001, pp. 1207–1212. IEEE.
37.
MeiTXGoodallRM (2001) Robust control for independently rotating wheelsets on a railway vehicle using practical sensors. IEEE Transactions on Control Systems Technology9(4): 599–607.
38.
NguyenSDNguyenQH (2017) Design of active suspension controller for train cars based on sliding mode control, uncertainty observer and neuro-fuzzy system. Journal of Vibration and Control23(8): 1334–1353.
39.
PatilUSuryawanshiHRengeM (2012) Performance comparison of DTC and FOC induction motor drive in five level diode clamped inverter. In: IEEE-international conference on advances in engineering, science and management (ICAESM-2012), Nagapattinam, Tamil Nadu, 30–31 March 2012, pp. 227–230. IEEE.
40.
Pérez-VenturaUFridmanL (2020) Chattering comparison between continuous and discontinuous sliding-mode controllers. In: Variable-Structure Systems and Sliding-Mode Control. London: Springer, pp. 197–211.
41.
PichlíkPZděnekJ (2014) Overview of slip control methods used in locomotives. Transactions on Electrical Engineering2: 38–43.
42.
PolachO (1992) Solution of wheel-rail contact forces suitable for calculation of rail vehicle dynamics. In: Second international conference on railway bogies, pp. 14–16. Budapest: Gépipari Tudomanyos Egyesület.
43.
PolachO (1999) A fast wheel-rail forces calculation computer code. Vehicle System Dynamics33(supp. 1): 728–739.
44.
PolachO (2005) Creep forces in simulations of traction vehicles running on adhesion limit. Wear258(7–8): 992–1000.
45.
RonankiDHemasundarAParthibanP (2013) A small 4-wheeler EV propulsion system using DTC controlled induction motor. In: Proceedings of the world congress on engineering, London, UK, 3–5 July 2013.
46.
RonankiDSinghSAWilliamsonSS (2017) Comprehensive topological overview of rolling stock architectures and recent trends in electric railway traction systems. IEEE Transactions on Transportation Electrification3(3): 724–738.
47.
SezerSAtalayAE (2011) Dynamic modeling and fuzzy logic control of vibrations of a railway vehicle for different track irregularities. Simulation Modelling Practice and Theory19(9): 1873–1894.
48.
ShimizuYOhishiKSanoT, et al. (2010) Anti-slip/slid re-adhesion control based on disturbance observer considering bogie vibration. Electrical Engineering in Japan172(2): 37–46.
49.
ShresthaSSpiryaginMWuQ (2019) Friction condition characterization for rail vehicle advanced braking system. Mechanical Systems and Signal Processing134: 106324.
50.
SivaprakasamAManigandanT (2015) An alternative scheme to reduce torque ripple and mechanical vibration in direct torque controlled permanent magnet synchronous motor. Journal of Vibration and Control21(5): 855–871.
51.
SongQSongYDCaiW (2011a) Adaptive backstepping control of train systems with traction/braking dynamics and uncertain resistive forces. Vehicle System Dynamics49(9): 1441–1454.
52.
SongQSongY-dTangT, et al. (2011b) Computationally inexpensive tracking control of high-speed trains with traction/braking saturation. IEEE Transactions on Intelligent Transportation Systems12(4): 1116–1125.
53.
TakahashiINoguchiT (1986) A new quick-response and high-efficiency control strategy of an induction motor. IEEE Transactions on Industry ApplicationsIA-22(5): 820–827.
54.
TakahashiIOhmoriY (1989) High-performance direct torque control of an induction motor. IEEE Transactions on Industry Applications25(2): 257–264.
55.
TakaokaYKawamuraA (2000) Disturbance observer based adhesion control for Shinkansen. In: Proceedings. 6th international workshop on advanced motion control, Nagoya, Japan, 30 March–1 April 2000, pp. 169–174. IEEE.
56.
TranMTAngKKLuongVH, et al. (2016) High-speed trains subject to abrupt braking. Vehicle System Dynamics54(12): 1715–1735.
57.
UnsalCKachrooP (1999) Sliding mode measurement feedback control for antilock braking systems. IEEE Transactions on Control Systems Technology7(2): 271–281.
58.
UtkinVLeeH (2006) Chattering problem in sliding mode control systems. In: International workshop on variable structure systems, 2006. VSS'06, Alghero, Sardinia, Italy, 5–7 June 2006, pp. 346–350. IEEE.
59.
VasićGFranklinFJFletcherDI (2011) Influence of partial slip and direction of traction on wear rate in wheel-rail contact. Wear270(3–4): 163–171.
60.
WangFZhangZMeiX, et al. (2018) Advanced control strategies of induction machine: Field oriented control, direct torque control and model predictive control. Energies11(1): 120.
61.
WuQSunYColeCM (2019) Railway track longitudinal force model. Vehicle System Dynamics: 1–16.
62.
XuZ-gBaiY-fWangH, et al. (2006) Fuzzy indirect adaptive adhesion control of electric locomotive [J]. Journal of System Simulation11: 047.
63.
YamazakiH-oKarinoYNagaiM, et al. (2005) Wheel slip prevention control by sliding mode control for railway vehicles (experiments using real size test equipment. System2: 1.
64.
YoungKDDrakunovSV (1992) Sliding mode control with chattering reduction. In: 1992 American control conference, Chicago, IL, USA, 24–26 June 1992, pp. 1291–1292. IEEE.
65.
YuanYHong-junZYe-mingL, et al. (2011) The dynamic study of locomotives under saturated adhesion. Vehicle System Dynamics49(8): 1321–1338.
66.
ZhangMBorjaPOrtegaR, et al. (2017) PID passivity-based control of port-Hamiltonian systems. IEEE Transactions on Automatic Control63(4): 1032–1044.
67.
ZhangMChenYSunX, et al. (2014) Particle-optimized control for automatic train operation based on sliding mode observer. In: Proceedings 2014 international conference on informative and cybernetics for computational social systems (ICCSS), Qingdao, China, 9–10 October 2014, pp. 79–84. IEEE.
68.
ZhangMShiPShenC, et al. (2019) Static output feedback control of switched nonlinear systems with actuator faults. IEEE Transactions on Fuzzy Systems: 1–1.
69.
ZinoberAS (1989) Deterministic control of uncertain systems. In: Proceedings. ICCON'89. IEEE international conference on. control and applications, Jerusalem, 3–6 April 1989, pp. 645–650. IEEE.
