DC-DC Linearized Converter Model for Faster Simulation of Lightweight Urban Electric Vehicles

11Citations
Citations of this article
51Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

The aim of this paper is to present a new bidirectional DC-DC linearized converter model for use in power demand and recovery units mainly used in Lightweight Electric Vehicle applications. The model significantly reduces the simulation time of the experiments performed, with up to a 4450-fold decrease in simulation times with respect to the original switched DC-DC topology. The study begins with a literature review of available switched converters, after which the presented topology is selected. The object-oriented modeling language Modelica® is used to implement the converter in the Dymola® modeling environment. Components and base classes from the Modelica Standard Library and VehicleInterfaces library are mainly used for better interoperability. Because of the intensive use of converters in the whole vehicle and the time consumed by the converter simulations due to high frequency commutation, a linearized DC-DC converter model is proposed. Comparison tests are performed between the reference switched models and the proposed linearized models in Dymola® tool to validate the linearized model behaviour. Nearly identical responses are obtained for both models, while simulation times are reduced as much as 1/4450 for the linearized converter. Furthermore, validation tests are carried out between the proposed linearized model in Dymola® and a reference switched model in LTspice® specific purpose simulation package for switched electronic circuits. Excellent agreement in the responses of both models is observed.

Cite

CITATION STYLE

APA

Gomez Navarro, F. J., Yebra, L. J., Gomez Medina, F. J., & Gimenez-Fernandez, A. (2020). DC-DC Linearized Converter Model for Faster Simulation of Lightweight Urban Electric Vehicles. IEEE Access, 8, 85380–85394. https://doi.org/10.1109/ACCESS.2020.2992558

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free