Fuel optimal controller for hydrostatic drives and real-world experiments on a wheel loader

Authors

  • Joni Backas Department of Intelligent Hydraulics and Automation, Tampere University of Technology, Tampere, Finland http://orcid.org/0000-0002-0553-5990
  • Reza Ghabcheloo Department of Intelligent Hydraulics and Automation, Tampere University of Technology, Tampere, Finland http://orcid.org/0000-0002-6043-4236
  • Seppo Tikkanen Department of Intelligent Hydraulics and Automation, Tampere University of Technology, Tampere, Finland http://orcid.org/0000-0003-2973-094X
  • Kalevi Huhtala Department of Intelligent Hydraulics and Automation, Tampere University of Technology, Tampere, Finland http://orcid.org/0000-0003-4055-0392

DOI:

https://doi.org/10.1080/14399776.2016.1202081

Keywords:

Fuel economy, power management, energy efficiency, power transmission, non-road mobile machinery

Abstract

In this study, we design a fuel optimal controller for hydrostatic drive transmissions (HSD) that significantly improves their fuel economy. Contrary to great proportion of the literature, efficacy of the controller is demonstrated by real machine implementation equipped with online fuel consumption measurement system. The main control objective of the devised controller is to minimise consumed fuel per travelled distance. Control commands are determined utilizing steady-state equations of the system, which facilitates real-time implementation. Dynamic situations are addressed with auxiliary functions running at higher frequency than the fuel economy part of the controller. The machine is a 5-ton wheel loader with pure HSD and no energy storage devices installed. In addition, all the components are commercially available. Thus, structure of the HSD and presented improvements in fuel economy are comparable to commercial machines and retrofitting existing drive-by-wire machinery with proposed controller will require little cost. The optimal controller is compared to a rule-based alternative that is based on a control method utilized in commercial wheel loaders. In autonomously driven drive cycles, measured total fuel consumption reduced up to 16.6% with the devised controller. In addition, the functionality of the controller is proven in extreme hill climbing tests.

Downloads

Download data is not yet available.

Author Biographies

Joni Backas, Department of Intelligent Hydraulics and Automation, Tampere University of Technology, Tampere, Finland

Joni Backas graduated (MSc) from Tampere University of Technology in 2010, majoring in machine automation. Currently, he is a PhD student at the Department of Intelligent Hydraulics and Automation (IHA). His research interests lie in the control of hydrostatic drive transmissions, especially improving their fuel economy.

Reza Ghabcheloo, Department of Intelligent Hydraulics and Automation, Tampere University of Technology, Tampere, Finland

Reza Ghabcheloo received his PhD degree from Technical University of Lisbon, Portugal in 2007. He is currently an associate professor with the Department of Intelligent Hydraulics and Automation, Tampere University of Technology, Finland. His research interests include guidance and motion control for mobile robots, and optimal motion planning and control in particular for energy efficiency of hydraulic powertrains.

Seppo Tikkanen, Department of Intelligent Hydraulics and Automation, Tampere University of Technology, Tampere, Finland

Seppo Tikkanen (MSc. 1995, Mech.Eng, Dr.Tech. 2000) is a professor of machine automation (energy efficient drives) in Department of Hydraulics and Automation at Tampere University of Technology. Previously he has worked as CTO at FIMECC Ltd., as group manager at Bosch Rexroth AG and as a researcher in Tampere University of Technology.

Kalevi Huhtala, Department of Intelligent Hydraulics and Automation, Tampere University of Technology, Tampere, Finland

Kalevi Huhtala was born in August 1957. Received his Dr.Tech. degree from Tampere University of Technology (Finland) in 1996. He is currently working as a professor in the Department of Intelligent Hydraulics and Automation (IHA) at Tampere University of Technology. He is also the head of the department. His primary research fields are intelligent mobile machines and diesel engine hydraulics.

References

Ahopelto, M., et al., 2013. Improved energy efficiency and

controllability of mobile work machines by reduced

engine rotational speed. Proceedings of the ASME 2013

international mechanical engineering congress & exposition,

IMECE2013, San Diego, California, USA.

Ahopelto, M., Backas, J., and Huhtala, K., 2012. Power

management in a mobile work machine: reduced diesel

rpm for better energy efficiency. Proceedings of the 7th

FPNI PhD Symposium on Fluid Power, June 27–30 2012,

Reggio Emilia, Italy.

Arcadis, 2010. Study in view of the revision of directive 97/68/

EC on non-road mobile machinery (NRMM) (module I - an

emissions inventory).

AVL, 2009. AVL product description KMA mobile [online].

Available from: https://www.avl.com/c/document_library/

get_file?uuid=168caf92-827a-44ab-9dd2-33281cb4eb3d

andgroupId=10138anddownload [Accessed 4 February

.

Backas, J., et al., 2011. IHA-machine: a future mobile machine.

The proceedings of the twelfth scandinavian international

conference on fluid power. Tampere, Finland.

Backas, J., Ghabcheloo, R., and Huhtala, K., 10–12 September

Fuel optimal controller for hydrostatic drives - a

simulation study and model validation. Proceedings of

the Bath/ASME 2014 symposium on fluid power & motion

control, Bath, United Kingdom.

Bosch Rexroth AG, 2003. Easy machine operation with

rexroth automotive drive and anti stall control. Elchingen:

Bosch Group.

Catepillar Inc., 2013. 336E H hydraulic excavator [online].

Available from: http://s7d2.scene7com/is/content/

Caterpillar/C811713 [Accessed 20 April 2016].

Daher, N. and Ivantysynova, M., 2014. Energy analysis of

an original steering technology that saves fuel and boosts

efficiency. Energy conversion and management, 86, 1059–

Deppen, T.O., Alleyne, A.G., Stelson, K.A. and Meyer, J.J.,

Optimal energy use in a light weight hydraulic

hybrid passenger vehicle. Journal of dynamic systems,

measurement, and control, 134 (4), 041009-1–041009-11.

doi:http://dx.doi.org/10.1115/1.4006082.

Deppen, T.O., et al., 2015. Comparative study of energy

management strategies for hydraulic hybrids. Journal

of dynamic systems, measurement, and control,

(4), 041002-1–041002-11. doi:http://dx.doi.

org/10.1115/1.4028525.

Eaton Corporation, 2007. ETAC: electronic transmission

automotive control user’s manual. Eden Prairie, MN: Eaton

Corporation.

Feng, D., Huang, D. and Li, D., 2011. Stochastic model

predictive energy management for series hydraulic

hybrid vehicle. Proceedings of the 2011 IEEE international

conference on mechatronics and automation, Beijing,

China.

Filipi, Z., et al., 2004. Combined optimisation of design and

power management of the hydraulic hybrid propulsion

system for the 6 × 6 medium truck. International journal

of heavy vehicle systems, 11 (3/4), 372–402.

Ghabcheloo, R., et al., 2009. Autonomous motion control

of a wheel loader. ASME dynamic systems and control

conference, Hollywood, CA, USA.

Hippalgaonkar, R. and Ivantysynova, M., 2012. Fuel savings of

a mini-excavator through a hydraulic hybrid displacement

controlled system. 8th international fluid power conference,

IFK, Dresden, Germany.

Huova, M., et al., 2010. Energy efficient control of

multiactuator digital hydraulic mobile machine. 7th

international fluid power conference, 7. IFK, Aachen,

Germany.

Jalil, N., Kheir, N., and Salman, M., 1997. A rule-based

energy management strategy for a series hybrid

vehicle. Proceedings of the American control conference,

Albuquerque, New Mexico.

Jähne, H., et al., 2008. Drive line simulation for increased

energy-efficiency of off-highway-machines. 6th international

fluid power conference, 6. IFK, Dresden, Germany.

KCMA Corporation, 2011. Kawasaki loaders,

CONEXPO 2011 handout [online]. Available from:

https://www.google.fi/url?sa=tandrct=jandq=andesrc=

sandsource=webandcd=7andved=0CDYQFjAGahUKEwi

AwZSgi7XHAhUF_HIKHdlrAGYandurl=http%3A%

F%2Fkawasakiloaders.com%2FdownloadFile.aspx%

F f i l e % 3 D % 2 Fp u b l i c % 2 F C on E x p o 2 0 1 1 %

Fpdf%2FKawasaki_CONEXPO_Handout.pdfandei=

j27UVcC9HoX4ywPZ1 [Accessed 19 August 2015].

Kermani, S., et al., 2011. Predictive energy management

for hybrid vehicle. Control engineering practice, 20 (4),

–420.

Korane, K., 2004. Machine design [online]. Available from:

http://machinedesign.com/archive/getting-more-mobilemachines

[Accessed 21 December 2015].

Kum, D., Peng, H., and Bucknor, N.K., 2011. Supervisory control

of parallel hybrid electric vehicles for fuel and emission

reduction. Journal of dynamic systems, measurement,

and control, 133 (6), 061010-1–061010-10. doi:

http://dx.doi.org/10.1115/1.4002708.

Kumar, R. and Ivantysynova, M., 2011. An instantaneous

optimization based power management strategy to reduce

fuel consumption in hydraulic hybrids. International

journal of fluid power, 12 (2), 15–25.

Luomaranta, M., 1999. A stable electrohydraulic load sensing

system based on a microcontroller. The proceedings of the

sixth Scandinavian international conference on fluid power,

–28 May 1999, Tampere, 419–432.

Meyer, J., et al., 2010. Power management strategy for

a parallel hydraulic hybrid passenger vehicle using

stochastic dynamic programming. Proceedings of the 7th

international fluid power conference, Aachen, Germany.

Opila, D., et al., 2013. Real-time implementation and

hardware testing of a hybrid vehicle energy management

controller based on stochastic dynamic programming.

Journal of dynamic systems, measurement, and control,

(2), 021002-1–021002-11. doi:http://dx.doi.

org/10.1115/1.4007238.

Paganelli, G., et al., 2001. General supervisory control policy

for the energy optimization of charge-sustaining hybrid

electric vehicles. JSAE review, 22 (4), 511–518.

Paganelli, G., et al., 2000. Simulation and assessment of power

control strategies for a parallel hybrid car. Proceedings of

the institution of mechanical engineers, part D: journal of

automobile engineering, 214 (7), 705–717.

Pfiffner, R., Guzzella, L., and Onder, C., 2003. Fuel-optimal

control of CVT powertrains. Control engineering practice,

(3), 329–336.

Sciarretta, A., Back, M., and Guzzella, L., 2004. Optimal

control of parallel hybrid electric vehicles. IEEE

transactions on control systems technology, 12 (3), 352–363.

Sciarretta, A. and Guzzella, L., 2007. Control of hybrid

electric vehicles. IEEE control systems magazine, 27 (2),

–70.

Serrao, L., Onori, S., and Rizzoni, G., 2011. A comparative

analysis of energy management strategies for hybrid

electric vehicles. Journal of dynamic systems, measurement,

and control, 133 (3), 031012-1–031012-11. doi:http://

dx.doi.org/10.1115/1.4003267.

Srivastava, N. and Haque, I., 2009. A review on belt and chain

continuously variable transmissions (CVT): dynamics

and control. Mechanism and machine theory, 44 (1),

–41.

The Lubrizol Corporation, 2013. John Deere adopts hybrid

technology [online]. Available from: http://drivelinenews.

com/off-highway-insights/john-deere-adopts-hybridtechnology/

[Accessed 19 August 2015].

Wang, Y., Zhang, H., and Sun, Z., 2013. Optimal control of

the transient emissions and the fuel efficiency of a diesel

hybrid electric vehicle. Proceedings of the institution

of mechanical engineers part D: journal of automobile

engineering, 227 (11), 1547–1561.

Williamson, C. A., 2010. Power management for multiactuator

mobile machines with displacement controlled

hydraulic actuators. Thesis (PhD). Purdue University.

Downloads

Published

2018-03-01

How to Cite

Backas, J., Ghabcheloo, R., Tikkanen, S., & Huhtala, K. (2018). Fuel optimal controller for hydrostatic drives and real-world experiments on a wheel loader. International Journal of Fluid Power, 17(3), 187–201. https://doi.org/10.1080/14399776.2016.1202081

Issue

Section

Original Article