Title :
Optimal Sizing of a Parallel PHEV Powertrain
Author :
Pourabdollah, Mitra ; Murgovski, Nikolce ; Grauers, Anders ; Egardt, Bo
Author_Institution :
Dept. of Signals & Syst., Chalmers Univ. of Technol., Gothenburg, Sweden
Abstract :
This paper introduces a novel method for the simultaneous optimization of energy management and powertrain component sizing of a parallel plug-in hybrid electric vehicle (PHEV). The problem is formulated as a convex optimization problem to minimize an objective function, which is a weighted sum of operational and component costs. The operational cost includes the consumed fossil fuel and electrical energy, whereas the component cost includes the cost of the battery, electric motor (EM), and internal combustion engine (ICE). The powertrain model includes quadratic losses for the powertrain components. Moreover, the combustion engine and the electric motor losses are assumed to linearly scale with respect to the size and the losses of baseline components. The result of the optimization is the variables of the global optimal energy management for every time instant and optimal component sizes. Due to the dependency of the result on the driving cycle, a long real-life cycle with its charging times is chosen to represent a general driving pattern. The method allows the study of the effect of some performance requirements, i.e., acceleration, top speed, and all-electric range, on the component sizes and total cost.
Keywords :
battery powered vehicles; convex programming; electric motors; hybrid electric vehicles; internal combustion engines; power transmission (mechanical); secondary cells; EM; ICE; component costs; convex optimization problem; electric motor; electrical energy; fossil fuel; global optimal energy management; internal combustion engine; objective function; optimal component sizes; optimal sizing; parallel PHEV powertrain components; parallel plug-in hybrid electric vehicle; Acceleration; Batteries; Energy management; Gears; Ice; Optimization; Vehicles; Convex optimization; energy management; hybrid electric vehicles; optimal control; sizing;
Journal_Title :
Vehicular Technology, IEEE Transactions on
DOI :
10.1109/TVT.2013.2240326