Fuzzy Control of the Length and Location of the Look-Ahead Window in a Look-Ahead Control Approach to Reduce Fuel Consumption in Rail Transportation

Authors

1 Assistant Professor‌, Department of Mechanical Engineering, Najafabad Branch, Islamic Azad University, Najafabad, Iran

2 Associate Professor, Faculty of Mechanical Engineering, Isfahan University of Technology, Isfahan, Iran

3 Assistant Professor, Faculty of Mechanical Engineering, Isfahan University of Technology, Isfahan, Iran

Abstract

Look-ahead control is a new approach for reducing fuel consumption in road and rail transportation industry. In this approach, considering the slope of ahead path, speed changes were decided on using a fuzzy controller so that, if there is an uphill on the ahead path, speed should be increased so that the vehicle could easily pass and fuel consumption is reduced. In the structure of this algorithm, a part of the ahead path is considered as a look-ahead window and the average slope of its inside points indicates the slope of the ahead path. Length of the look-ahead window and its distance from the vehicle's instantaneous location are two main parameters of look-ahead algorithms that affect their performance. In this paper, unlike the previous studies in which length and location of the look-ahead window kept constant during the whole path, these two parameters changed dynamically by a fuzzy controller according to the speed of the vehicle and slope variance of the points inside the window. Results of the simulation of train motion using the proposed algorithm demonstrated better performance of the algorithm and increased fuel efficiency.
 

Keywords

References

B. M. Baumann, G. Washington, B. C. Glenn, and G. Rizzoni (2000), “Mechatronic design and control of hybrid electric vehicles”, IEEE/ASME Transactions on Mechatronics, vol. 5, no. 1, pp. 58-72.
-   T. Teratani, K. Kuramochi, H. Nakao, T. Tachibana, K. Yagi, and S. Abou (2003),”Development of Toyota mild hybrid system (THS-M) with 42v power net”, Electric Machines and Drives Conference, IEEE International, Vol. 1, pp. 3-10 
-Krug.A (­2006), “Railroad Facts and Figures”.
 -Howlett. P., Pudney. P., Vu. X. (2009), “Local energy minimization in optimal train control”, Automatica, Vol. 45,
pp. 2692-2698.
-S. E. Plotkin (2009), “Examining fuel economy and carbon standards for light vehicles," Energy Policy, Vol. 37, No. 10, pp. 3843-3853.
-Hellström. E., Ivarsson. M., Åslund.J., Nielsen. L., (2009), “Look-ahead control for heavy trucks to minimize trip time and fuel consumption”, Control Engineering Practice, Vol.17, No.2, pp. 245-254.
-Ganji. B., Kouzani. A., (2010), “A Study on look-ahead control and energy management strategies in hybrid electric vehicles” 2010 8th IEEE International Conference on Control and Automation Xiamen, China.
-Hellstr¨om. E. Aslund. J., Nielsen. L., (2010), “Design of an efficient algorithm for fuel-optimal look-ahead control”, Control Engineering Practice, vol. 18, pp.­1318–1327.
      -Ganji. B, Kouzani. A., Hessami. M., (2011), “Backward modeling and look-ahead fuzzy energy management controller for a parallel hybrid vehicle”, Control and Intelligent Systems, Vol. 39, No. 3.
-Khayyam.H, Nahavandi.S, Hu.E, Kouzani.A, Chonka.A, Abawajy.J, Marano.V, Davis.S (2011) “Intelligent energy management control of vehicle air conditioning via look-ahead System”, Applied Thermal Engineering, vol. 31,
pp. 3147-3160.
- Khayyam, H., A., Nahavandi, S., b., Sam Davis c., (2012), “ Adaptive cruise control look-ahead system for energy management of vehicles”, Expert Systems with Applications 39, 3874–3885.
-Saadat M., Esfahanian M, Saket M. (2014), “Fuzzy Look-Ahead Control Optimization for Diesel Locomotives Energy Consumption”, Proceedings of the ASME  8th International Conference on Energy Sustainability & 12th Fuel Cell Science, Engineering and Technology Conference
ESFuel Cell, June 29-July2, Boston, Massachusetts, USA.
 
Journal of Transportation Research
Volume 15, Issue 4
December 2019
Pages 275-283

Files

Share

How to cite

Statistics