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The Impact of the Drive Mode of a Hybrid Drive System on the Share of Electric Mode in the RDC Test
Technical Paper
2020-01-2249
ISSN: 0148-7191, e-ISSN: 2688-3627
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Abstract
The share of hybrid and electric powertrains in the market increases continuously. In local driving conditions, electric vehicles are zero-emission, yet their regular use requires an infrastructure allowing the recharging of high-voltage batteries. Hybrid vehicles also allow the use of the electric drive; however, when the high-voltage battery is low, a combustion engine is used to recharge it. Hybrid powertrains do not require any changes in the infrastructure, nor do they force any changes in the driver's habits. The use of a hybrid vehicle may, however, reduce the operating time of the combustion engine, thus contributing to the reduction of fuel consumption. This reduction of fuel consumption results from a specifically selected energy flow strategy in hybrid systems. This strategy was the focus of the research performed to identify the energy flow conditions in a hybrid drive system under driving conditions corresponding to the RDE test. A Ford Fusion vehicle was tested in two drive modes determining the related energy flow conditions, including the operating conditions of the electric motors, the combustion engine and the battery. The energy balance was determined to take into account the high-voltage battery discharge and charging energy as well as the energy recovered during regenerative braking. It was found that under the RDC test conditions, the vehicle operates in the electric mode for over 40% of the distance and 65% of the drive time, with the energy balance of the vehicle being positive (SOCend > SOCstart). Additionally, it was indicated that the time operated in the electric mode when driving in urban conditions is approx. 80% and decreases to approx. 20% for highway conditions.
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Cieslik, W., Zawartowski, J., and Fuc, P., "The Impact of the Drive Mode of a Hybrid Drive System on the Share of Electric Mode in the RDC Test," SAE Technical Paper 2020-01-2249, 2020, https://doi.org/10.4271/2020-01-2249.Data Sets - Support Documents
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