Abstract
Hybrid electric vehicles are being developed to reduce the pollutant emissions and the fossil-fuel consumption of transportation. Innovative technologies are inserted to improve the performance of hybrid vehicles, including trucks and buses. Thereby, trends towards gear shifting automation motivate the research on replacing a discrete conventional Automated Manual Transmission (AMT) with a Continuously Variable Transmission (CVT). Theoretically, such a transmission enables better operation points of the thermal engine, and therefore a reduction of its fuel consumption and emissions. However, the conventional (hydraulic actuated) CVT efficiency during quasi-stationary operation is typically lower than the efficiency of a classical discrete gearbox, which leads to higher fuel consumption. This paper is focused on the study of the interests of a CVT for a medium-duty Hybrid Electric Truck (HET). The complete model and control of CVT-based and AMT-based HET are described in a unified way using Energetic Macroscopic Representation (EMR). These models are transformed to backward-models to be computed by the Dynamic Programming Method (DPM). Such a method leads to define the (off-line) optimal energy management strategies for a fair comparison of both hybrid trucks. For the studied driving cycle, the hybridization allows a fuel saving of 10% with an AMT and 3% with a CVT. The fuel consumption is higher for the CVT-based HET in comparison with the AMT-based HET due to the lowest efficiency of the CVT (85%) compared to the AMT (around 92%). However, future (on-demand) CVTs with an increased efficiency could be a solution of interest to reduce the fuel consumption of such applications. The developed method can be used to test these new CVTs, other vehicles or other driving cycles.
Original language | English |
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Pages (from-to) | 120-129 |
Number of pages | 10 |
Journal | Mathematics and Computers in Simulation |
Volume | 158 |
DOIs | |
Publication status | Published - Apr 2019 |
Bibliographical note
Funding Information:This paper has been achieved within the framework of CE2I project (Convertisseur d’Énergie Intégré Intelligent). CE2I is co-financed by European Union with the financial support of European Regional Development Fund (ERDF) , French State and the French Region of “Hauts-de-France” .
Keywords
- Continuous variable transmission
- Dynamic programming method
- Energetic macroscopic representation
- Hybrid electric truck