A Multi-Disciplinary Optimization Approach for Lightweighting and Performance Improvement of Electric Light Commercial Vehicle

Abstract

<div class="section abstract"><div class="htmlview paragraph">Rapid Urbanisation, in recent times, has created an exponential demand for light commercial vehicles. Electric vehicles are seen as a way to reduce the impact of emissions due to transportation in urban areas. Due to the growth of e-commerce, commercial transportation, and particularly last-mile delivery, is anticipated to increase. In this context, electric light commercial vehicles (eLCVs) have the potential to be a promising solution by tackling the emission impacts, ensuring faster delivery along with ideal running costs and payload capacity. To increase the range of electric vehicles, it has to be designed for lighter weight with optimal performance in order to meet the user requirements. Cargo capacity and payload have to be taken into account while design &amp; validating the vehicle structure under static and dynamic conditions. Simulation driven product development will help the design team to account for the possible design failure cases at system and vehicle level. However, all these cases are multi-disciplinary and require validating the individual design verification plans (DVPs) of each discipline. Optimizing the performance of all these cases individually and provide design solutions will result in the increase of product development timelines. Structural Design verification plans for three disciplines a) Crash / Safety, b) Durability / Reliability, c) NVH / Comfort will be discussed in this work to meet the system and vehicle objectives. A Multi-Disciplinary Optimization (MDO) approach is explained which will provide upfront feasible design routes considering various disciplines performance targets and weight targets at systems level, based on the severity and importance of the system.</div></div>