Abstract: A major barrier in consumer adoption of electric vehicles (EVs) is “range anxiety,â€‌ the concern that the vehicle will run out of power at an inopportune time. Range anxiety is caused by the current relatively low ...

Abstract: We compare the performance of human players against that of the efficient global optimization (EGO) algorithm for an NPcomplete powertrain design and control problem. Specifically, we cast this optimization problem as an ...

Abstract: Effective electrification of automotive vehicles requires designing the powertrain's configuration along with sizing its components for a particular vehicle type. Employing planetary gear (PG) systems in hybrid electric ...

Abstract: Car sharing services promise “green” transportation systems. Two vehicle technologies offer marketable, sustainable sharing: autonomous vehicles (AVs) eliminate customer requirements for car pick-up and return, and battery ...

Abstract: Existing hybrid powertrain architectures, i.e., the connections from engine and motors to the vehicle output shaft, are designed for particular vehicle applications, e.g., passenger cars or city buses, to achieve good fuel ...

Abstract: Manufacturers must decide when to invest and launch a new vehicle segment or how to redesign vehicles existing segment under market uncertainties. We present an optimization framework for redesigning or investing in future ...

Abstract: Crowdsourced evaluation is a promising method of evaluating engineering design attributes that require human input. The challenge is to correctly estimate scores using a massive and diverse crowd, particularly when only a ...

Abstract: Quantitative preference models are used to predict customer choices among design alternatives by collecting prior purchase data or survey answers. This paper examines how to improve the prediction accuracy of such models ...

Abstract: Computational simulation models support a rapid design process. Given model approximation and operating conditions uncertainty, designers must have confidence that the designs obtained using simulations will perform as ...

Abstract: Multiobjective design optimization studies typically derive Pareto sets or use a scalar substitute function to capture design trade-offs, leaving it up to the designer’s intuition to use this information for design refinements ...