Abstract
The hybrid powertrain is a promising concept to contribute to achieve future CO2-targets. This paper describes a method to improve future automotive powertrains efficiently in real world driving conditions. Beside the optimization of the internal combustion engine and the electric components, the operating strategy of the hybrid powertrain is of particular importance to minimize the vehicles fuel consumption. A combination of start/stop operation, downspeeding, load-point shifting and pure electric driving can provide substantial fuel savings compared to conventional powertrains. However, in addition to the fuel consumption the more and more stringent future emission legislation must be taken into the account when optimizing the operating strategy. A fast light-off of the catalytic converters and a control of the converter temperatures during pure electric driving must be achieved. Therefore, numerous parameters have to be optimized simultaneously to realize the best solution for the hybrid powertrain. A numerical optimization approach was used to define the operating strategies efficiently for the mentioned goals. The results of this optimization were compared to the fuel consumption and the exhaust emissions of the conventional powertrain. The potential of a further strategy optimisation could be evaluated. Generally, it could be shown that long phases of electric driving combined with aggressive load point shifting to balance the battery’s state of charge are most favorable in terms of efficiency. The phases of electric driving are additionally limited by the temperature drop of the catalysts and the lack of pollutant conversion after restart. This is a new and innovative approach to develop electrified powertrains efficiently. Finally it can be stated, that the numerical optimization method proved to be a powerful tool to support the development process of hybrid powertrains with numerous degrees of freedom.
F2012-B02-023
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Jefferson CM, Barnard RH (2002) Hybrid vehicle propulsion. WIT Press, Southampton, UK, pp 1–27
Planer M, Zahradnik F (2012) Hybrid power plant development: engine-in-the-loop—integration of combustion engine and HiL simulation. The ETAS Group Magazine—Real Times
van Basshuysen R (2007) Ottomotor mit direkteinspritzung. Vieweg Verlag, 1. Auflage, pp 205–211, ISBN 978-3-8348-0202-6
Salmasi FR (2007) Control strategies for hybrid electric vehicles: evolution, classification, comparison, and future trends. IEEE Trans Veh Technol 56(5)
Pisu P, Rizzoni G (2007) A comparative study of supervisory control strategies for hybrid electric vehicles. IEEE Trans Control Syst Technol 15(3)
Sundström O, Guzzella L, Soltic P (2008) Optimal hybridization in two parallel hybrid electric vehicles using dynamic programming. In: Proceedings of the 17th world congress, the international federation of automatic control, Seoul, Korea, July 6–11
Krenek T, Ruthmair M, Raidl G, Planer M (2012) Applying (hybrid) metaheuristics to fuel consumption optimization of hybrid electric vehicles. J Appl Evol Comput, pp 376–385
Nelder JAuMR (1965) A simplex method for function minimization. Oxford J: Comput J, Brit Comput Soc 7(4):308–313
Michalewicz Z (1996) Heuristic methods for evolutionary computation techniques. J Heuristics 1(2):177–206
Kennedy J, Eberhart R (1995) Particle swarm optimization. In: Proceedings of the IEEE international conference on neural networks 4:1942–1948
Helm S, Schneeweiss B, Winter S, Kozek M (2008) Hardware in the loop simulation of a hybrid powertrain. In: Proceedings of the international simulation multi-conference, Scotland, pp 16–19
Schneeweiss B, Teiner P (2010) Evaluation of NOx and fuel consumption reduction potential of parallel diesel-hybrid powertrains using engine-in-the-loop simulation. SAE Technical Paper 2010-32-0128. doi: 10.4271/2010-32-0128
Planer M, Krenek T, Lauer T, Geringer B (2012) Optimisation of hybrid strategies with heuristic algorithm. In: 12th Stuttgart international symposium automotive and engine technology, FKSF—Research Institute of Automotive Engineering and Vehicle Engines, Stuttgart
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Planer, M., Krenek, T., Lauer, T., Felix, Z., Geringer, B., Back, M. (2013). Optimization of Hybrid Strategies with Heuristic Algorithms to Minimize Exhaust Emissions and Fuel Consumption. In: Proceedings of the FISITA 2012 World Automotive Congress. Lecture Notes in Electrical Engineering, vol 191. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33777-2_25
Download citation
DOI: https://doi.org/10.1007/978-3-642-33777-2_25
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-33776-5
Online ISBN: 978-3-642-33777-2
eBook Packages: EngineeringEngineering (R0)