Reduction of Pneumatic Tyred Roller Fuel Consumption

Abstract:

This article deals with optimization of operational parameters of an energy regeneration module for a heavy vehicle. Recently, there was developed an energy regeneration module for a pneumatic tyred roller with hydrostatic drive. It was necessary to optimize its operational parameters to achieve good results in experimental tests on the actual vehicle. The optimization process was based on a numerical model of the vehicle using a parallelized modification of the differential evolution algorithm as an optimizer. Suggested parameter values were subsequently verified experimentally on the vehicle by analysis of the fuel consumption.

• Periodical: Applied Mechanics and Materials (Volume 821)
• Pages: 614-619
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.821.614
• Online since: January 2016
• Authors: Tomáš Panáček*, Milan Klapka
• Keywords: Evolutionary Algorithms, Kinetic Energy Regeneration, Numerical Simulation, Optimization

References

[1] Baseley, S., Ehret, C., Greif, E., &Kliffken, M. Hydraulic Hybrid Systems for Commercial Vehicles. SAE Technical Paper 2007-01-4150, doi: 10. 4271/2007-01-4150. (2007).

DOI: 10.4271/2007-01-4150

[2] J. Nevrlý, Z. Němec, P. Noskievič, Use of Matlab/Simulink and Amesim for simulation of hydraulic recovery of kinetic energy. In Proceedings of The 4th International conference ANTiM, University UNION – Nikola Tesla, Belgrade, Serbia (2014).

[3] T. Panáček, M. Klapka, Z. Němec, Optimization of valve manifold timing sequence using differential evolution algorithm. In Engineering mechanics 2014, Book of full texts. Prague: Institute of Termomechanics, Academy of Sciences of the Czech Republic, pp.468-471 (2014).

[4] J. Nevrlý, Z. Němec, Valve timing of recovery module of road roller. Hydraulika a pneumatika, 2014, vol. 31, nr. 1, pp.8-12. ISSN: 1335- 5171 (2014).

[5] A. Pourmovahed, N. H. Beachley, F. J. Fronczak, Modelling of a hydraulic energy regeneration system - part I: Analytical treatment. ASME J. Dyn. Sys., Meas., and Control, Vol. 114. pp.155-159 (1992).

DOI: 10.1115/1.2896497

[6] A. Pourmovahed, N. H. Beachley, F. J. Fronczak, Modelling of a hydraulic energy regeneration system - part II: Experimental program. ASME J. Dyn. Sys., Meas., and Control. Vol. 114. pp.160-165, (1992).

DOI: 10.1115/1.2896498

[7] P. L. Matheson, J. S. Stecki, Optimisation of a hybrid diesel-hydraulic automotive powertrain using ADVISOR, Matlab & Simulink. In Australian J. Mech. Eng., pp.43-50. Engineers media for engineers, Australia. (2005).

DOI: 10.1080/14484846.2005.11464479

[8] X. Wang, J. Jiang, Optimization Matching of Wheel Drive Hydraulic Hybrid Vehicle Components Based on Adaptive Simulated Annealing Genetic Algorithm, Proceedings of the 2009 IEEE International Conference on Mechatronics and Automation, pp.1962-1967. (2009).

DOI: 10.1109/icma.2009.5244986

[9] X. Wang, Y. Ancai, Ch. Wie, Optimal Matching on Driving System of Hydraulic Hybrid Vehicle. In Procedia Engineering, Elsevier, Vol. 15, p.5294–5298. ISSN 1877-7058. doi: 10. 1016/j. proeng. 2011. 08. 981 (2011).

DOI: 10.1016/j.proeng.2011.08.981

[10] R. Storn, Differential Evolution for Continuous Function Optimization [online] (cit. 2. 8. 2013). Available on http: /www. icsi. berkeley. edu/~storn/code. html.