Development of a Predictive Control Function for a Plug-in Hybrid Electric Vehicle with Electrically-heated Catalyst

This master thesis work is focused on the development of a predictive EHC control function for a diesel plug-in hybrid electric vehicle equipped with a EURO 7 compliant exhaust aftertreatment system (EATS), with the purpose of showing the advantages provided by the implementation of a predictive control strategy with respect to a rule-based one. A preliminary step will be the definition of an accurate powertrain and EATS physical model, starting from already existing and validated applications. Then, a rule-based control strategy managing the torque split between the electric motor (EM) and the internal combustion engine (ICE) will be developed and calibrated, with the main target of limiting tailpipe NOx emission by taking into account EM and ICE operating conditions together with EATS conversion efficiency. The information available from vehicle connectivity will be used to reconstruct the future driving scenario, also referred to as electronic horizon (eHorizon), and in particular to predict ICE first start. Based on this knowledge, an EATS pre-heating phase can be planned to avoid low pollutant conversion efficiencies, thus preventing high NOx emission due to engine cold start. Consequently, the final NOx emission over the complete driving cycle will be strongly reduced, allowing to comply with the limits potentially set by the incoming EURO 7 regulation. Moreover, given the same NOx emission target, the gain achieved thanks to the implementation of an EHC predictive control function will allow to consider a simplified EATS layout, thus reducing the related manufacturing cost. The promising results achieved in terms of NOx emission reduction show the effectiveness of the application of a predictive control strategy focused on EATS thermal management and highlight the potential of a complete integration and parallel development of involved vehicle physical systems, control software and connectivity data management.

Cure Induced Residual Stresses on Thick Composite Components Manufactured by Additive Process

This study investigates the effect of an additive process in manufacturing of thick composites. Airstone 780 E epoxy resin and 785H Hardener system is used in the analysis since it is widely used wind turbine blade, namely thick components. As a fiber, fabric by SAERTEX (812 g/m2) with a 0-90 degrees layup direction is used. Temperature overshoot is a major issue during the manufacturing of thick composites. A high temperature overshoot leads to an increase in residual stresses. These residual stresses are causing warping, delamination, dimensional instability, and undesired distortion of composite structures. A coupled thermo-mechanical model capable of predicting cure induced residual stresses have been built using the commercial FE software Abaqus®. The possibility of building thick composite components by means of adding a finite number of sub-laminates has been investigated. The results have been compared against components manufactured following a standard route. The influence of pre-curing of the sub-laminates has also been addressed and results compared with standard practice. As a result of the study, it is found that introducing additive process can prevent temperature overshoot to occur and benefits the residual stresses generation during the curing process. However, the process time required increases by 50%, therefore increasing the manufacturing costs. An optimized cure cycle is required to minimize process time and cure induced defects simultaneously.