Advancing the life cycle energy optimisation methodology
Abstract: The Life Cycle Energy Optimisation (LCEO) methodology aims at finding a design solution that uses a minimum amount of cumulative energy demand over the different phases of the vehicle's life cycle, while complying with a set of functional constraints. This effectively balances trade-offs, and therewith avoids sub-optimal shifting between the energy demand for the cradle-to-production of materials, operation of the vehicle, and end-of-life phases. This work further develops the LCEO methodology and expands its scope through three main methodological contributions which, for illustrative purposes, were applied to a vehicle sub-system design case study.An End-Of-Life (EOL) model, based on the substitution with a correction factor method, is included to estimate the energy credits and burdens that originate from EOL vehicle processing. Multiple recycling scenarios with different levels of assumed induced recyclate material property degradation were built, and their impact on the LCEO methodology's outcomes was compared to that of scenarios based on landfilling and incineration with energy recovery. The results show that the inclusion of EOL modelling in the LCEO methodology can alter material use patterns and significantly effect the life cycle energy of the optimal designs.Furthermore, the previous model is expanded to enable holistic vehicle product system design with the LCEO methodology. The constrained optimisation of a vehicle sub-system, and the design of a subset of the processes which are applied to it during its life cycle, are simultaneously optimised for a minimal product system life cycle energy. In particular, a subset of the EOL processes' parameters are considered as continuous design variables with associated barrier functions that control their feasibility. The results show that the LCEO methodology can be used to find an optimal design along with its associated ideal synthetic EOL scenario. Moreover, the ability of the method to identify the underlying mechanisms enabling the optimal solution's trade-offs is further demonstrated.Finally, the functional scope of the methodology is expanded through the inclusion of shape-related variables and aerodynamic drag estimations. Here, vehicle curvature is taken into account in the LCEO methodology through its impact on the aerodynamic drag and therewith its related operational energy demand. In turn, aerodynamic drag is considered through the estimation of the drag coefficient of a vehicle body shape using computational fluid dynamics simulations. The aforementioned coefficient is further used to estimate the energy required by the vehicle to overcome aerodynamic drag. The results demonstrate the ability of the LCEO methodology to capitalise on the underlying functional alignment of the structural and aerodynamic requirements, as well as the need for an allocation strategy for the aerodynamic drag energy within the context of vehicle sub-system redesign.Overall, these methodological developments contributed to the exploration of the ability of the LCEO methodology to handle life cycle and functional trade-offs to achieve life cycle energy optimal vehicle designs.
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