Abstract

The series–parallel architecture is the most interesting for hybrid electric vehicles, allowing the lowest fuel consumption. Unlike passenger cars, this architecture is not commercially available on the heavy-duty vehicles market. This is due to technical limitations associated with unsufficient load capability of the geartrain. To address this issue, new transmissions, such as the electrical variable transmission, have been developed. The novelty of this paper relies on the hybridization of a long-haul truck using the electrical variable transmission. This study aims to investigate the potential of using this new transmission for trucks. For that aim, fuel consumption benchmarking of three powertrain topologies is performed, considering: (a) a gearless topology; (b) a geared topology that uses one gearbox inserted between the engine and the mechanical input port of the electrical variable transmission; (c) a geared topology similar to the second one, but, with an additional multi-stage gearbox inserted to the mechanical output port of the electrical variable transmission. For a fair comparison between the different topologies, a bi-level optimization process has been used, incorporating the optimization of both components sizing and control. Results show that the fuel consumption of the gearless powertrain is higher than the engine-powered truck due to higher losses in the electrical variable transmission. While maximum fuel reduction of 14.2% was obtained by a geared topology that uses two gearboxes. Furthermore, emphasis is given to understand the effect of the powertrain component sizing on fuel consumption. Depending on the defined sizing, a possible fuel reduction is achieved from 3.3% to 14.2% for the two geared topologies. The reduction of CO2 emissions is found to be proportional to the fuel savings. Considering a long-haul mission, the last findings prove that the electrical variable transmission exhibits potential to reduce fuel consumption, if an adequate powertrain topology and its sizing are well defined.

Full Text
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