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Climate change due to greenhouse gas emissions has led to new vehicle emissions standards which in turn have led to a call for vehicle technologies to meet these standards. Modeling of vehicle fuel consumption and emissions emerged as an effective tool to help in developing and assessing such technologies, to help in predicting aggregate vehicle fuel consumption and emissions, and to complement traffic simulation models. The paper identifies the current state of the art on vehicle fuel consumption and emissions modeling and its utilization to test the environmental impact of the Intelligent Transportation Systems (ITS)’ measures and to evaluate transportation network improvements. The study presents the relevant models to ITS in the key classifications of models in this research area. It demonstrates that the trends of vehicle fuel consumption and emissions provided by current models generally do satisfactorily replicate field data trends.

A hybrid search optimization is presented in order to optimize hybrid laminated fibrous composite E-springs for vehicle suspension systems. This optimization is conducted with both of the geometrical configuration and laminate structure of the E-spring. A genetic algorithm along with a hill-climbing random-walk approach are used through a developed NURBS-based technique in order to conduct this optimization. A mathematical-modeling-based mid-ware technology is introduced in order to fully automate the optimization process through linking the run engines of mathematical modeling and finite element analysis from within the mathematical modeling engine. A hybrid approach of the inter-laminar shear stress and Tsai-Wu criteria is first implemented in order to identify failure indices of the resulting optimum shape and laminate structure.