Fuzzy Nonlinear Programming Based Life Cycle Cost Optimization for Hybrid Electric Vehicles

Abstract

Hybrid electric vehicle technologies are extensively attracted to researchers for the environmental consciousness of related fields in recent years. HEV gain the benefit of both gasoline engines and electric motors. They are developed and configured to achieve various objectives, such as improved fuel economy, increased power, and lowered emission. Design of the hybrid electric vehicle systems involves the selection of components and configurations to fulfill the required functional and performance specifications which is especially crucial for these complex systems with large numbers of subsystems and components. Reliability allocation and optimization have been widely studied and applied to system design in various technological areas, including electrical, electronic, mechanical, and etc. The objective of this study is to provide an availability allocation of maintainability and reliability model and a design algorithm which allows for partial malfunctions of the power system without stalling the vehicle and furthermore consider the fuzziness on the life cycle costs of its components in the design process. This availability design strategy will provide hybrid electric vehicle developer a better alternative to design and produce new products with much lower cost and better competitiveness.