Reducing Vehicle Weight and Improving U.S. Energy Efficiency Using Integrated Computational Materials Engineering

Transportation accounts for approximately 28% of U.S. energy consumption with the majority of transportation energy derived from petroleum sources. Many technologies such as vehicle electrification, advanced combustion, and advanced fuels can reduce transportation energy consumption by improving the efficiency of cars and trucks. Lightweight materials are another important technology that can improve passenger vehicle fuel efficiency by 6–8% for each 10% reduction in weight while also making electric and alternative vehicles more competitive. Despite the opportunities for improved efficiency, widespread deployment of lightweight materials for automotive structures is hampered by technology gaps most often associated with performance, manufacturability, and cost. In this report, the impact of reduced vehicle weight on energy efficiency is discussed with a particular emphasis on quantitative relationships determined by several researchers. The most promising lightweight materials systems are described along with a brief review of the most significant technical barriers to their implementation. For each material system, the development of accurate material models is critical to support simulation-intensive processing and structural design for vehicles; improved models also contribute to an integrated computational materials engineering (ICME) approach for addressing technical barriers and accelerating deployment. The value of computational techniques is described by considering recent ICME and computational materials science success stories with an emphasis on applying problem-specific methods.

[1]  Paul E. Krajewski,et al.  Microstructure-based multiscale modeling of elevated temperature deformation in aluminum alloys , 2010 .

[2]  L. Hector,et al.  Quantitative prediction of solute strengthening in aluminium alloys. , 2010, Nature materials.

[3]  Nicholas Lutsey,et al.  Review of technical literature and trends related to automobile mass-reduction technology , 2010 .

[4]  A. Saeed-Akbari,et al.  Characterization and Prediction of Flow Behavior in High-Manganese Twinning Induced Plasticity Steels: Part I. Mechanism Maps and Work-Hardening Behavior , 2012, Metallurgical and Materials Transactions A.

[5]  Yucong Wang,et al.  Advances in Computational Tools for Virtual Casting of Aluminum Components , 2011 .

[6]  Mei Li,et al.  Virtual aluminum castings: An industrial application of ICME , 2006 .

[7]  Stephen Zoepf,et al.  Automotive Features: Mass Impact and Deployment Characterization , 2011 .

[8]  Elmar Beeh,et al.  Super Light Car—lightweight construction thanks to a multi-material design and function integration , 2009 .

[9]  O. Kintzel,et al.  Experimental and numerical lifetime assessment of Al 2024 sheet , 2012 .

[10]  Mark W. Verbrugge,et al.  Optimizing Battery Sizing and Vehicle Lightweighting for an Extended Range Electric Vehicle , 2011 .

[11]  Zi-kui Liu,et al.  First-principles calculations of impurity diffusion coefficients in dilute Mg alloys using the 8-frequency model , 2011 .

[12]  Emmanuel P Kasseris,et al.  On the Road in 2035 : Reducing Transportation ’ s Petroleum Consumption and GHG Emissions , 2008 .

[13]  Engineering,et al.  First-principles data for solid-solution strengthening of magnesium: From geometry and chemistry to properties , 2010, 1007.2585.

[14]  Lynette W. Cheah,et al.  Cars on a diet : the material and energy impacts of passenger vehicle weight reduction in the U.S. , 2010 .