Abstract

The present study has focused on the refinement of a previously developed tool for the optimization of the layout of hybrid electric vehicles and on its application to a newly proposed non-plug in parallel hybrid vehicle, which has been equipped with a planetary gear set and a single-speed gearbox positioned between a compression ignition engine and a permanent magnet electric machine. This vehicle is capable of torque-coupling and speed-coupling between the engine and the electric machine, and for this reason has been referred to as a “dual-mode vehicle”.The tool performs a bi-level (nested) coupling of design and control strategy optimization, and is able to identify the optimal design of each hybrid vehicle by minimizing the powertrain costs over a 10-year time span. The vehicle design determines the size of battery, engine and electric machine, as well as the values of the speed ratio of each power coupling device. Different powertrain cost definitions, which account for the production costs of the components and the operating costs related to fuel consumption and battery depletion over the lifetime of the vehicle, have been proposed. The latter cost contribution depends directly on the control strategy adopted to manage the power flow between the electric machine and the engine, as well as on the selection of the transmission gear. The optimal control strategy has been identified using a specifically developed fast running dynamic programming-based optimizer, which minimizes an objective function over a given training driving mission.The performance of the dual-mode vehicle with the optimal layout has been investigated in detail over several driving missions and compared with that of more traditional hybrid vehicles equipped with either a speed coupling device or with a torque coupling device, as well as with a conventional reference vehicle.Moreover, several sensitivity analyses have been carried out in order to investigate the impact of the cost definition, of the objective function and of the training driving mission on the powertrain design and on its performance (fuel economy, pollutant emissions, battery management).Finally, different market scenarios have been explored, in terms of fuel price, battery life and battery cost, and their effects on the identification of the optimal design, as well as on the performance of the resulting vehicles, have been analyzed.

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