Energy-Based Design of Powertrain for a Re-Engineered Post-Transmission Hybrid Electric Vehicle

Laura Tribioli
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Laura Tribioli: Department of Engineering, Niccolò Cusano University, via Don Carlo Gnocchi 3, 00166 Rome, Italy

Energies, 2017, vol. 10, issue 7, 1-22

Abstract: This paper presents a systematic approach for the design of post-transmission hybrid electric vehicle powertrains, as an instrument aiding the designer in making the right decision. In particular, a post-transmission series/parallel hybrid electric powertrain is considered, and all of the possible energy paths are taken into account, in order to automatically select the configuration that gives the lowest fuel consumption, thus better fitting to the considered mission. The optimization problem is solved with the Dijkstra algorithm, which is more computationally efficient than other optimization algorithms in the case of massive design spaces. In this way, it is possible to design a vehicle in terms of architecture and component sizes, without making any a priori choices, which are usually based on common sense, likely compromising the overall system efficiency. In order to demonstrate the effectiveness of the methodology, different driving cycles have been simulated, and some results are presented. The methodology is particularly applied to re-engineered vehicles, aimed at maximizing the benefits of the vehicle hybridization process. Results show how the introduction, in the optimization algorithm, of the engine load factor and sharing factor, for the engine torque split between the generator and the wheels, is crucial. For example, a 10% reduction of the original engine size, suggested by a low load factor, is able to allow for a 24% reduction in the fuel consumption. On the other hand, the sharing factor is of particular importance in suggesting if the vehicle architecture should be series, parallel or rather combined.

Keywords: hybrid electric vehicle; powertrain design; component sizing; optimal design methodology (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (8)

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