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Multi‐objective modeling and analysis of an electric pickup vehicle for range, performance, drivability, handling and ride comfort attributes
Author(s) -
Dharumaseelan Elavarasan,
Pitchaikani Anand,
Tamilselvam Elanchezhian,
Sundstrom Peter,
Malik Sidharth
Publication year - 2019
Publication title -
incose international symposium
Language(s) - English
Resource type - Journals
ISSN - 2334-5837
DOI - 10.1002/j.2334-5837.2019.00675.x
Subject(s) - powertrain , automotive engineering , chassis , automotive industry , battery electric vehicle , engineering , range (aeronautics) , electric vehicle , truck , simulation , computer science , mechanical engineering , torque , thermodynamics , power (physics) , physics , quantum mechanics , aerospace engineering
In today's electric vehicle arena, range, performance, drivability, handling safety and ride comfort are few important attributes an OEM would like to improve on a vehicle. However, they are almost mutually exclusive like greater range & extreme handling safety would need to compromise on drivability & ride comfort and vice versa respectively. Automotive engineers constantly focus on to find the right balance among these attributes by optimum design of the vehicle components. Often these components are multi‐disciplinary involving different engineering domains like mechanical, thermal, electrical, hydraulic & electronics, etc. These complexities demand for model based and systems engineering approach from the start of the development. This emphasizes the need for high fidelity, dynamic vehicle system models suitable for co‐development of different components and controls. In this study, detailed vehicle model representing an electric pickup truck including battery, traction motors, driveline, chassis (suspension, brakes, wheels & mounts) is created in Modelica platform using which multiple vehicle level attributes like range, performance, drivability, handling and ride comfort are studied. Further, it is shown that the simulation speed can be increased by varying fidelity of the subsystems based on study intended within the same model framework.