Multi-Frequency Averaging (MFA) Model of Electric-Hybrid Powertrain Suitable for Variable Frequency Operation Applied in Geographically-Distributed Power Hardware-in-the-Loop (GD-PHiL) Simulation

Sen, Surojit; Evans, Paul L.; Johnson, C. Mark

Abstract

© 2018 IEEE Project aims to develop capability for OEMs and suppliers to 'virtually-connect' multiple prototype powertrain components (engine, motor-drive etc.) and engage in real-time system simulation, thereby reducing cost by eliminating co-location dependency. Technical challenge faced is to duplicate test-hardware state & performance at remote location(s) real-time via an indeterminate internet connection characteristic of latency and jitter. MFA-based remote model is a potential solution but applied research till date has been for fixed-frequency operation. This paper explores variable frequency operation of MFA and outlines the implementation of generic electric powertrain intended for remote control/operation, indicating key performance improvements over time-domain switching models.

Citation

Sen, S., Evans, P. L., & Johnson, C. M. (2018, August). Multi-Frequency Averaging (MFA) Model of Electric-Hybrid Powertrain Suitable for Variable Frequency Operation Applied in Geographically-Distributed Power Hardware-in-the-Loop (GD-PHiL) Simulation. Presented at 2018 IEEE Vehicle Power and Propulsion Conference (VPPC), Chicago, IL, USA

• Presentation Conference Type: Edited Proceedings
• Conference Name: 2018 IEEE Vehicle Power and Propulsion Conference (VPPC)
• Start Date: Aug 27, 2018
• End Date: Aug 30, 2018
• Acceptance Date: Jun 25, 2018
• Online Publication Date: Jan 10, 2019
• Publication Date: 2018-08
• Deposit Date: Jan 31, 2019
• Publicly Available Date: Jan 31, 2019
• Pages: 1-6
• Series ISSN: 1938-8756
• Book Title: Proceedings - 2018 IEEE Vehicle Power and Propulsion Conference (VPPC)
• ISBN: 978-1-5386-6204-5
• DOI: https://doi.org/10.1109/VPPC.2018.8604967
• Keywords: geographically; distributed, simulation, automotive, electric, vehicle, powertrain,; modeling
• Public URL: https://nottingham-repository.worktribe.com/output/1510504
• Publisher URL: https://ieeexplore.ieee.org/document/8604967
• Additional Information: © 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
• Contract Date: Jan 31, 2019