Topological analysis of powertrains for refuse-collecting vehicles based on real routes – Part I: Hybrid hydraulic powertrain
Journal Article (2016)
International Journal of Automotive Technology
Moreno-Eguilaz, Juan Manuel
Álvarez Flórez, Jesús Andrés
In this two-part paper, a topological analysis of powertrains for refuse-collecting vehicles (RCVs) based on the simulation of different architectures (internal combustion engine, hybrid electric, and hybrid hydraulic) on real routes is proposed. In this first part, a characterization of a standard route is performed, analyzing the average power consumption and the most frequent working points of an internal combustion engine (ICE) in real routes. This information is used to define alternative powertrain architectures. A hybrid hydraulic powertrain architecture is proposed and modelled. The proposed powertrain model is executed using two different control algorithms, with and without predictive strategies, with data obtained from real routes. A calculation engine (an algorithm which runs the vehicle models on real routes), is presented and used for simulations. This calculation engine has been specifically designed to analyze if the different alternative powertrain delivers the same performance of the original ICE. Finally, the overall performance of the different architectures and control strategies are summarized into a fuel and energy consumption table, which will be used in the second part of this paper to compare with the different architectures based on hybrid electric powertrain. The overall performance of the different architectures indicates that the use of a hybrid hydraulic powertrain with simple control laws can reduce the fuel consumption up to a 14%.
Engines, Hybrid Power Vehicle, Energy Management Optimization, Drive Cycle Prediction
F. Soriano, J.M. Moreno-Eguilaz, J.A. Álvarez and J. Riera. Topological analysis of powertrains for refuse-collecting vehicles based on real routes – Part I: Hybrid hydraulic powertrain. International Journal of Automotive Technology, 17(5): 873-882, 2016.