Electric Vehicle Architecture Design Based on Database

The purpose of this study is to extend the mileage by improving the efficiency of the electric vehicle (EV) driving and thermal management system (TMS). The powertrain system and the TMS must be considered simultaneously from the architecture stage as complementary systems to maintain the driving performance of the EV. This paper proposes an EV architectural design method and a multi-physical EV modeling technique. The main components of the EV are standardized differently from those of the internal combustion engine (ICE) vehicle, and the TMS is designed by thermal system configuration. Therefore, instead of the traditional continuous variable-based design methodology, optimal combination design based on the component database (DB) and the configuration plot presents the combinational design method. The performance of an EV varies depending on the performance of driving components and TMS, and weather. This paper presents a Modelica-based vehicle modeling technique to integrate multiple physical phenomena. Finally, we implemented an automated design using the optimal combination design method and the multi-physical integrated vehicle model design framework. The design of the C-segment EV was carried out to review the validity of the proposed method. 2880 laboratories were planned and designed using design variables with 10 levels of mixing. As a result of the design, we have confirmed that the mileage increases by 5% compared to the previous one in NEDC mode.