Figure 1.
Mechanical Load Dynamic Emulation Control System
-
Previous Article
Major project risk assessment method based on BP neural network
- DCDS-S Home
- This Issue
-
Next Article
Error minimization with global optimization for difference of convex functions
August & September
2019, 12(4&5): 1035-1052.
doi: 10.3934/dcdss.2019071
A novel road dynamic simulation approach for vehicle driveline experiments
| 1. | Key Laboratory of Advanced Manufacture Technology for Automobile Parts, Ministry of Education, Chongqing University of Technology, Chongqing 400054, China |
| 2. | Chongqing Tsingshan Industrial, Chongqing 402761, China |
| 3. | Chongqing Vocational Institute of Engineering, Chongqing 402260, China |
| 4. | Chongqing Tsingshan Industrial, Chongqing 402761, China |
| 5. | Chongqing Academy of Science and Technology, Chongqing 401123, China |
A dynamic simulation approach for performing emulation experiments on vehicle driveline test bench is discussed in this paper. In order to reduce costs and shorten new vehicle development cycle time, vehicle simulation on the driveline test bench is an attractive alternative at the development phase to reduce the quantity of proto vehicles. This test method moves the test site from the road to the bench without the need for real chassis parts. Dynamic emulation of mechanical loads is a Hardware-in-the-loop (HIL) procedure, which can be used as a supplement of the conventional simulations in testing of the operation of algorithms without the need for the prototypes. The combustion engine is replaced by a electric drive motor, which replicates the torque and speed signature of an actual engine, The road load resistance of the vehicle on a real test road is accurately simulated on load dynamometer motor. On the basis of analyzing and comparing the advantages and disadvantages of the inverse dynamics model and the forward model based on speed closed loop control method, in view of the high order, nonlinear and multi variable characteristics of test bench system, a load simulation method based on speed adaptive predictive control is presented. It avoids the complex algorithm of closed loop speed compensation, and reduces the influence of inaccurate model parameters on the control precision of the simulation system. The vehicle start and dynamic shift process were simulated on the test bench.
Keywords:
Simulation,
speed adaptive predictive control,
acceleration resistance,
inertia simulation.
Mathematics Subject Classification:
Primary: 58F15, 58F17; Secondary: 53C35.
Citation:
Wen-Li Li, Jing-Jing Wang, Xiang-Kui Zhang, Peng Yi. A novel road dynamic simulation approach for vehicle driveline experiments. Discrete & Continuous Dynamical Systems - S,
2019, 12
(4&5)
: 1035-1052.
doi: 10.3934/dcdss.2019071
![]()
References:
| [1] |
R. Ahlawat, S. Jiang and D. Medonza, et al., Engine torque pulse and wheel slip emulation for transmission-in-the-loop experiments, 2010 IEEE/ASME International Conference on Advanced Intelligent Mechatronics Montréal, Canada, 2010, 688-695. Google Scholar |
| [2] |
Z. H. Akpolat, G. M. Asher and J. C. Clare, A practical approach to the design of robust speed controllers for machine drives, IEEE Trans. on Industrial Electronics, 47 (2000), 315-324. Google Scholar |
| [3] |
Z. H. Akpolat, G. M. Asher and J. C. Clare, Dynamic emulation of mechanical loads using a vector controlled induction motor-generator set, IEEE Trans. on Industrial Electronics, 46 (1999), 370-379. Google Scholar |
| [4] |
J. Arellano-Padilla, G. Asher and M. Sumner, Control of an ac-dynamometer for dynamic emulation of mechanical loads with stiff and flexible shafts, IEEE Transactions on Industrial Electronics, 53 (2006), 1250-1260. Google Scholar |
| [5] |
M. Corbett, P. Lamm and J. McNichols, et. al., Effects of transient power extraction on an integratated hardware-in-the-loop aircraft/propulsion/power system, Power Systems Conference. Washington, SAE Internatinal, 2008, Paper No. 2008-01-2926. Google Scholar |
| [6] |
Z. Hakan Akpolat, G. M. Ashen and J. C. Clare, Dynamic emulation of mechanical Loads using a vector-controlled induction motor-generator set, IEEE Transactions on Industrial Lectornics, 46 (1999), 370-379. Google Scholar |
| [7] |
Z. Hakan Akpolat, G. M. Ashen and J. C. Clare, Experimental dynamometer emulation of nonlinear mechanical loads, Industry Applications Society Annual Meeting. St. Louis. IEEE transactions on industrial Applications, 35 (1999), 1367-1373. Google Scholar |
| [8] |
Z. Hakan Akpolat, G. Asher and J. Clare, Experimental dynamometer emulation of nonlinear mechanical loads, The 1998 IEEE Industry Applications Conference. St. Louis, 1998, 532-539. Google Scholar |
| [9] |
C. Hewson, G. Asher and M. Sumner, Dynamometer control for emulation of mechanical loads, The 1998 IEEE Industry Applications Conference. St. Louis, 1998, 1511-1518. Google Scholar |
| [10] |
S. Jiang, M. H. Smith and J. Kitchen, et al., Development of an engine-in-the-loop vehicle simulation system in engine dynamometer test cell, SAE 2009 World Congress & Amp, Exhibition, United States, SAE International 2009, Paper No 2009-01-1039. Google Scholar |
| [11] |
S. Kaatz, T. Abe and W. Vanhaaften, et al., The ford motor company transmission NVH test cell, Noise & Vibration Conference and Exhibition. Michigan. SAE Internatinal, 2003, Paper No. 2003-01-1681. Google Scholar |
| [12] |
Z.-J. Liu, J.-J. Hu and S. Wen, et al., Design of data acquisition and communication system for AMT comprehensive performance testbench, Journal of Chongqing University: Natural Science Edition, 32 (2009), 775-781. Google Scholar |
| [13] |
N. Newberger, T. A. Nevius and P. Lasota, et al., Virtual engine dynamometer in service life testing of transmissions: A comparison between real engine and electric dynamometers as prime movers in validation test rigs, Extending Dynamometer Performance for Virtual Engine Simulation. International Congress and Exposition, SAE Internatinal, 2010, Paper No. 2010-01-0919. Google Scholar |
| [14] |
R. W. Newton, R. E. Betz and H. B. Penfold, Emulating dynamics load characteristics using a dynamic dynamometer, Proc. Int. Conf. Power Electron. and Drive Syst., 1 (1995), 465-470. Google Scholar |
| [15] |
M. Rodic, K. Jezernik and M. Trlep, Use of dynamic emulation of mechanical loads in the design of adjustable speed applications, Advanced Motion Control, AMC, Kawasaki, 2004, 677-682. Google Scholar |
| [16] |
M. Rodi$\check{c}$, K. Jezernik and M. Trlep, Dynamic emulation of mechanical loads: And advanced approach, IEE Proc., Electr. Power Appl., 153 (2006), 159-166. Google Scholar |
| [17] |
M. Rodi$\check{c}$, K. Jezernik and M. Trlep, A feedforward approach to the dynamic emulation of mechanical loads, Proceedings of the 35th Annual IEEE Power Electronics Specialists Conference(PESC'04), (2004), 4595-4601. Google Scholar |
| [18] |
W.-J. Wang, W.-G. Zhang and X. Li, Inertia electrical emulation and angular acceleration estimation for transmission test rig, Journal of Southeast University(Natural Science Edition), 42 (2012), 62-66. Google Scholar |
show all references
References:
| [1] |
R. Ahlawat, S. Jiang and D. Medonza, et al., Engine torque pulse and wheel slip emulation for transmission-in-the-loop experiments, 2010 IEEE/ASME International Conference on Advanced Intelligent Mechatronics Montréal, Canada, 2010, 688-695. Google Scholar |
| [2] |
Z. H. Akpolat, G. M. Asher and J. C. Clare, A practical approach to the design of robust speed controllers for machine drives, IEEE Trans. on Industrial Electronics, 47 (2000), 315-324. Google Scholar |
| [3] |
Z. H. Akpolat, G. M. Asher and J. C. Clare, Dynamic emulation of mechanical loads using a vector controlled induction motor-generator set, IEEE Trans. on Industrial Electronics, 46 (1999), 370-379. Google Scholar |
| [4] |
J. Arellano-Padilla, G. Asher and M. Sumner, Control of an ac-dynamometer for dynamic emulation of mechanical loads with stiff and flexible shafts, IEEE Transactions on Industrial Electronics, 53 (2006), 1250-1260. Google Scholar |
| [5] |
M. Corbett, P. Lamm and J. McNichols, et. al., Effects of transient power extraction on an integratated hardware-in-the-loop aircraft/propulsion/power system, Power Systems Conference. Washington, SAE Internatinal, 2008, Paper No. 2008-01-2926. Google Scholar |
| [6] |
Z. Hakan Akpolat, G. M. Ashen and J. C. Clare, Dynamic emulation of mechanical Loads using a vector-controlled induction motor-generator set, IEEE Transactions on Industrial Lectornics, 46 (1999), 370-379. Google Scholar |
| [7] |
Z. Hakan Akpolat, G. M. Ashen and J. C. Clare, Experimental dynamometer emulation of nonlinear mechanical loads, Industry Applications Society Annual Meeting. St. Louis. IEEE transactions on industrial Applications, 35 (1999), 1367-1373. Google Scholar |
| [8] |
Z. Hakan Akpolat, G. Asher and J. Clare, Experimental dynamometer emulation of nonlinear mechanical loads, The 1998 IEEE Industry Applications Conference. St. Louis, 1998, 532-539. Google Scholar |
| [9] |
C. Hewson, G. Asher and M. Sumner, Dynamometer control for emulation of mechanical loads, The 1998 IEEE Industry Applications Conference. St. Louis, 1998, 1511-1518. Google Scholar |
| [10] |
S. Jiang, M. H. Smith and J. Kitchen, et al., Development of an engine-in-the-loop vehicle simulation system in engine dynamometer test cell, SAE 2009 World Congress & Amp, Exhibition, United States, SAE International 2009, Paper No 2009-01-1039. Google Scholar |
| [11] |
S. Kaatz, T. Abe and W. Vanhaaften, et al., The ford motor company transmission NVH test cell, Noise & Vibration Conference and Exhibition. Michigan. SAE Internatinal, 2003, Paper No. 2003-01-1681. Google Scholar |
| [12] |
Z.-J. Liu, J.-J. Hu and S. Wen, et al., Design of data acquisition and communication system for AMT comprehensive performance testbench, Journal of Chongqing University: Natural Science Edition, 32 (2009), 775-781. Google Scholar |
| [13] |
N. Newberger, T. A. Nevius and P. Lasota, et al., Virtual engine dynamometer in service life testing of transmissions: A comparison between real engine and electric dynamometers as prime movers in validation test rigs, Extending Dynamometer Performance for Virtual Engine Simulation. International Congress and Exposition, SAE Internatinal, 2010, Paper No. 2010-01-0919. Google Scholar |
| [14] |
R. W. Newton, R. E. Betz and H. B. Penfold, Emulating dynamics load characteristics using a dynamic dynamometer, Proc. Int. Conf. Power Electron. and Drive Syst., 1 (1995), 465-470. Google Scholar |
| [15] |
M. Rodic, K. Jezernik and M. Trlep, Use of dynamic emulation of mechanical loads in the design of adjustable speed applications, Advanced Motion Control, AMC, Kawasaki, 2004, 677-682. Google Scholar |
| [16] |
M. Rodi$\check{c}$, K. Jezernik and M. Trlep, Dynamic emulation of mechanical loads: And advanced approach, IEE Proc., Electr. Power Appl., 153 (2006), 159-166. Google Scholar |
| [17] |
M. Rodi$\check{c}$, K. Jezernik and M. Trlep, A feedforward approach to the dynamic emulation of mechanical loads, Proceedings of the 35th Annual IEEE Power Electronics Specialists Conference(PESC'04), (2004), 4595-4601. Google Scholar |
| [18] |
W.-J. Wang, W.-G. Zhang and X. Li, Inertia electrical emulation and angular acceleration estimation for transmission test rig, Journal of Southeast University(Natural Science Edition), 42 (2012), 62-66. Google Scholar |
Figure 2.
Inverse Dynamic Model
Figure 3.
Speed Closed Loop Control Algorithm
Figure 4.
Speed closed loop control with feed-forward compensation
Figure 5.
Speed Closed-loop Control with Feed-forward Compensation
Figure 6.
Speed adaptive predictive control
Figure 7.
Schematic diagram of vehicle acceleration resistance
Figure 8.
Control model of speed adaptive predictive control
Figure 9.
The characteristic curves of drive motor and engine
Figure 10.
The characteristic curves of load motor
Figure 11.
Simulation range of electrical inertia on the platform system
Figure 12.
Acceleration inertia simulation curve
Figure 13.
The setup of vehicle driveline test bench
Figure 14.
The clutch control unit of the test bench
Figure 15.
The starting characteristics curves of simulated vehicle
Figure 16.
The shift control unit of the test bench
Figure 17.
Dynamic simulation curves of upshift
Figure 18.
Dynamic simulation curves of downshift
Figure 19.
Dynamic simulation curves of continuous shifting process
Table 1.
The technical data of drive motor
| Power (Kw) |
Frequency (Hz) |
Torque |
Speed (r/min) |
Moment of inertia (kg |
| 235.6 | 250 | 360 | 5000 | 0.042 |
| Power (Kw) |
Frequency (Hz) |
Torque |
Speed (r/min) |
Moment of inertia (kg |
| 235.6 | 250 | 360 | 5000 | 0.042 |
Table 2.
The technical data of load motor
| Power (Kw) |
Frequency (Hz) |
Torque ( |
Speed (r/min) |
Moment of inertia (kg |
| 310 | 27.2 | 3701 | 800 | 6.3 |
| Power (Kw) |
Frequency (Hz) |
Torque ( |
Speed (r/min) |
Moment of inertia (kg |
| 310 | 27.2 | 3701 | 800 | 6.3 |
| [1] |
João M. Lemos, Fernando Machado, Nuno Nogueira, Luís Rato, Manuel Rijo. Adaptive and non-adaptive model predictive control of an irrigation channel. Networks & Heterogeneous Media, 2009, 4 (2) : 303-324. doi: 10.3934/nhm.2009.4.303 |
| [2] |
Luís Tiago Paiva, Fernando A. C. C. Fontes. Sampled–data model predictive control: Adaptive time–mesh refinement algorithms and guarantees of stability. Discrete & Continuous Dynamical Systems - B, 2019, 24 (5) : 2335-2364. doi: 10.3934/dcdsb.2019098 |
| [3] |
Gongfa Li, Wei Miao, Guozhang Jiang, Yinfeng Fang, Zhaojie Ju, Honghai Liu. Intelligent control model and its simulation of flue temperature in coke oven. Discrete & Continuous Dynamical Systems - S, 2015, 8 (6) : 1223-1237. doi: 10.3934/dcdss.2015.8.1223 |
| [4] |
Linhao Xu, Marya Claire Zdechlik, Melissa C. Smith, Min B. Rayamajhi, Don L. DeAngelis, Bo Zhang. Simulation of post-hurricane impact on invasive species with biological control management. Discrete & Continuous Dynamical Systems - A, 2020, 40 (6) : 4059-4071. doi: 10.3934/dcds.2020038 |
| [5] |
Cristina Anton, Jian Deng, Yau Shu Wong, Yile Zhang, Weiping Zhang, Stephan Gabos, Dorothy Yu Huang, Can Jin. Modeling and simulation for toxicity assessment. Mathematical Biosciences & Engineering, 2017, 14 (3) : 581-606. doi: 10.3934/mbe.2017034 |
| [6] |
Hassan Khassehkhan, Messoud A. Efendiev, Hermann J. Eberl. A degenerate diffusion-reaction model of an amensalistic biofilm control system: Existence and simulation of solutions. Discrete & Continuous Dynamical Systems - B, 2009, 12 (2) : 371-388. doi: 10.3934/dcdsb.2009.12.371 |
| [7] |
Gong Chen, Peter J. Olver. Numerical simulation of nonlinear dispersive quantization. Discrete & Continuous Dynamical Systems - A, 2014, 34 (3) : 991-1008. doi: 10.3934/dcds.2014.34.991 |
| [8] |
Ingenuin Gasser, Marcus Kraft. Modelling and simulation of fires in tunnel networks. Networks & Heterogeneous Media, 2008, 3 (4) : 691-707. doi: 10.3934/nhm.2008.3.691 |
| [9] |
Nicolas Vauchelet. Numerical simulation of a kinetic model for chemotaxis. Kinetic & Related Models, 2010, 3 (3) : 501-528. doi: 10.3934/krm.2010.3.501 |
| [10] |
Petr Bauer, Michal Beneš, Radek Fučík, Hung Hoang Dieu, Vladimír Klement, Radek Máca, Jan Mach, Tomáš Oberhuber, Pavel Strachota, Vítězslav Žabka, Vladimír Havlena. Numerical simulation of flow in fluidized beds. Discrete & Continuous Dynamical Systems - S, 2015, 8 (5) : 833-846. doi: 10.3934/dcdss.2015.8.833 |
| [11] |
Ingenuin Gasser. Modelling and simulation of a solar updraft tower. Kinetic & Related Models, 2009, 2 (1) : 191-204. doi: 10.3934/krm.2009.2.191 |
| [12] |
Rudy R. Negenborn, Peter-Jules van Overloop, Tamás Keviczky, Bart De Schutter. Distributed model predictive control of irrigation canals. Networks & Heterogeneous Media, 2009, 4 (2) : 359-380. doi: 10.3934/nhm.2009.4.359 |
| [13] |
Lars Grüne, Marleen Stieler. Multiobjective model predictive control for stabilizing cost criteria. Discrete & Continuous Dynamical Systems - B, 2019, 24 (8) : 3905-3928. doi: 10.3934/dcdsb.2018336 |
| [14] |
Torsten Trimborn, Lorenzo Pareschi, Martin Frank. Portfolio optimization and model predictive control: A kinetic approach. Discrete & Continuous Dynamical Systems - B, 2019, 24 (11) : 6209-6238. doi: 10.3934/dcdsb.2019136 |
| [15] |
Marilena Filippucci, Andrea Tallarico, Michele Dragoni. Simulation of lava flows with power-law rheology. Discrete & Continuous Dynamical Systems - S, 2013, 6 (3) : 677-685. doi: 10.3934/dcdss.2013.6.677 |
| [16] |
Arno F. Münster. Simulation of stationary chemical patterns and waves in ionic reactions. Discrete & Continuous Dynamical Systems - B, 2002, 2 (1) : 35-46. doi: 10.3934/dcdsb.2002.2.35 |
| [17] |
Ana I. Muñoz, José Ignacio Tello. Mathematical analysis and numerical simulation of a model of morphogenesis. Mathematical Biosciences & Engineering, 2011, 8 (4) : 1035-1059. doi: 10.3934/mbe.2011.8.1035 |
| [18] |
Dianmo Li, Zengxiang Gao, Zufei Ma, Baoyu Xie, Zhengjun Wang. Two general models for the simulation of insect population dynamics. Discrete & Continuous Dynamical Systems - B, 2004, 4 (3) : 623-628. doi: 10.3934/dcdsb.2004.4.623 |
| [19] |
Thomas G. Hallam, Qingping Deng. Simulation of structured populations in chemically stressed environments. Mathematical Biosciences & Engineering, 2006, 3 (1) : 51-65. doi: 10.3934/mbe.2006.3.51 |
| [20] |
Andriy Sokolov, Robert Strehl, Stefan Turek. Numerical simulation of chemotaxis models on stationary surfaces. Discrete & Continuous Dynamical Systems - B, 2013, 18 (10) : 2689-2704. doi: 10.3934/dcdsb.2013.18.2689 |
2018 Impact Factor: 0.545
Tools
Metrics
Other articles
by authors
[Back to Top]