Assessment of Minimum Fuel Consumption Operation Strategy for Hybrid Powersport Drive-Trains by Means of Dynamic Programming Method 2016-32-0015
The hybrid-electric drivetrain permits a multitude of new control strategies like brake energy recuperation, engine start-stop operation, shifting of engine working point, as well as in some situations pure electric driving. Overall this typically allows a reduction of fuel consumption and therefore of carbon dioxide emissions. During the development process of the vehicle various drivetrain configurations have to be considered and compared. This includes decisions regarding the topology - like the position of the electrical machine in the drivetrain (e.g. at the gearbox input or output shaft), as well as the selection of the needed components based on their parameters (nominal power, energy content of the battery, efficiency etc.). To compare the chosen variants, typically the calculated fuel consumption for a given driving cycle is used. For this simulation an energy management strategy is needed, which defines the power distribution between ICE, electric machine and mechanical brakes. However, the used operation strategy has a large influence on the achieved fuel consumption. Typically used online strategies (rule based approaches, neural networks, … ) have to be adapted for each configuration individually. Nevertheless, it cannot be guaranteed, that the individually optimized controllers work equally well for each configuration. To circumvent this problem, we use a mathematical method (so called dynamic programming) to calculate an optimal energy management for each considered configuration. This optimum represents a set of operation modes and operation points, which lead to the absolute minimum fuel consumption. Thereby a comparison of different configurations without influence of the control strategy becomes possible.
Citation: Schweighofer, B., Wegleiter, H., Zisser, M., Rieger, P. et al., "Assessment of Minimum Fuel Consumption Operation Strategy for Hybrid Powersport Drive-Trains by Means of Dynamic Programming Method," SAE Technical Paper 2016-32-0015, 2016, https://doi.org/10.4271/2016-32-0015. Download Citation
Bernhard Schweighofer, Hannes Wegleiter, Michael Zisser, Paul Rieger, Christian Zinner, Stephan Schmidt
Graz University of Technology, Austria
SAE/JSAE 2016 Small Engine Technology Conference & Exhibition