Harmonizing Aerodynamic Efficiency, Stability, and Acoustic Excellence: Multi-Objective Optimization for Electric Vehicle Rear-End Design

Abstract

In recent years, the automotive field has exposed a significant surge in electrification, presenting a pivotal solution to environmental concerns. However, addressing the challenge of driving mileage remains a critical aspect in the realm of electric vehicles (EVs). Among the various factors influencing battery energy consumption during operation, aerodynamic force emerges as a primary contributor. Mitigating this force holds the key to substantial improvements in driving mileage, making it a focal point of exploration in this research. The impact of aerodynamic force extends beyond mere energy consumption; it intricately influences battery size, vehicle mileage, performance, stability, and passenger comfort. Navigating this multifaceted terrain poses a formidable challenge for automotive engineers engaged in the development of electric vehicles. This study undertakes the optimization of rear-end design factors for a hatchback electric vehicle, specifically addressing drag, lift, and aerodynamic noise objectives. Five critical geometric factors of the rear end – Rear Spoiler Length, Rear Spoiler Angle, Rear Diffuser Angle, Boat Tail Angle, and 5th Door Height – are identified as key design parameters. The interplay of these factors and their impact on objectives is systematically investigated through a Design of Experiment (DoE) approach. To enhance the efficiency of the investigation, a fractional factorial design method is utilized, effectively reducing the number of individual case studies. The formulation of regression equations, capturing the essence of significant terms for each objective, lays the groundwork for a subsequent multi-objective optimization process. This optimization, driven by the maximization of a composite desirability function, identifies optimal levels for each design factor. The research culminates in the selection of a model with optimum rear-end factors based on a comprehensive evaluation of drag, lift, and aerodynamic noise objectives. The aerodynamic performance surrounding this optimal model is intricately described, offering valuable insights into the holistic impact of the chosen design parameters on the electric vehicle's aerodynamics.