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The design of a hybrid electric powertrain requires a complex optimization procedure because its performance will strongly depend on both the size of the components and the energy management strategy. The problem is particular critical in the aircraft field because of the strong constraints to be fulfilled (in particular in terms of weight and volume). The problem was addressed in the present investigation by linking an in-house simulation code for hybrid electric aircraft with a commercial many-objective optimization software. The design variables include the size of engine and electric motor, the specification of the battery (typology, nominal capacity, bus voltage), the cooling method of the motor and the battery management strategy. Several key performance indexes were suggested by the industrial partner. The four most important indexes were used as fitness functions: electric endurance, fuel consumption, take-off distance and powertrain volume.

The optimization procedure adopted in the present investigation is based on Genetic Algorithms (GA) and allows different fitness functions to be simultaneously maximized. The parameters to be optimized are related to the geometric features of the combustion chamber, which ranges of variation are very wide. For all the investigated configurations, bowl volume and squish-to-bowl volume ratio were kept constant so that the compression ratio was the same for all investigated chambers. This condition assures that changes in the emissions were caused by geometric variations only. The spray injection angle was also considered as a variable parameter. The optimization was simultaneously performed for different engine operating conditions, i.e. load and speed, and the corresponding fitness values were weighted according to their occurrence in the European Driving Test.

The effect of the shape of the bowl on the combustion process and emissions of a Natural Gas - Diesel dual fuel engine is analyzed. The simulation of the dual fuel combustion is performed with a modified version of the KIVA3V code where diesel is treated as the main fuel and a further reacting specie is introduced as methane (CH4). The auto-ignition of the pilot is simulated with a modified version of the Shell model and the first stage of the combustion, related to the pilot burning process, is simulated with the Characteristic Time Combustion model. When the temperature of the mixture reaches a certain threshold, a kernel of combustion is initialized. Until the kernel reaches a nominal radius the combustion of CH4 is prevented. The combustion of CH4 is simulated with a turbulent characteristic time too. Numerical models were chosen as a compromise between accuracy and computational time.

The present study aims at the implementation of a Matlab/Simulink environment to assess the performance (thrust, specific fuel consumption, aircraft/engine mass, cost, etc.) and environmental impact (greenhouse and pollutant emissions) of conventional and more electric aircrafts. In particular, the benefits of adopting more electric solutions for either aircrafts at given missions specifications can be evaluated. The software, named PLA.N.E.S, includes a design workflow for the input of aircraft specification, kind of architecture (e.g. series or parallel) and for the definition of each component including energy converter (piston engine, turboprop, turbojet, fuel cell, etc.), energy storage system (batteries, super-capacitors), auxiliaries and secondary power systems. It is also possible to setup different energy management strategies for the optimal control of the energy flows among engine, secondary equipment and storage systems during the mission.

An analytical methodology to efficiently evaluate design alternatives in the conversion of a Common Rail Diesel engine to either CNG dedicated or dual fuel engine has been presented in a previous investigation. The simulation of the dual fuel combustion was performed with a modified version of the KIVA3V code including a modified version of the Shell model and a modified Characteristic Time Combustion model. In the present investigation, this methodology has been validated at two levels. The capability of the simulation code in predicting the emissions trends when changing pilot specification, like injected amount, injection pressure and start of injection, and engine configuration parameters, like compression ratio and axial position of the diesel injector has been verified. The second validation was related to the capability of the proposed computer-aided procedure in finding optimal solutions in a reduced computational time.