Online Signal-Based Fault Detection and Diagnosis of EV Inverter during WLTP Driving Cycle

Fernando Alvarez-Gonzalez; Andres Sierra-Gonzalez; Elena Trancho; Miguel Allende Marcos

doi:10.1109/VPPC53923.2021.9699360

Online Signal-Based Fault Detection and Diagnosis of EV Inverter during WLTP Driving Cycle

Fernando Alvarez-Gonzalez
, Andres Sierra-Gonzalez
, Elena Trancho
, Miguel Allende Marcos

ACS

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

4 Citations (Scopus)

Abstract

Recently, transport electrification has undergone a dramatic expansion. This is generating an increasing demand for powertrain reliability. Furthermore, the recent adoption of wide bandgap (WBG) devices, pushes this need even more, particularly for power electronics. This manuscript addresses this need by combining simple and computationally light signal-based fault detection and diagnosis (FDD) methods. These are tested online by simulating electric vehicle (EV) three-phase inverter faults during standardized driving cycles. Simulations are carried out including a three-phase interior permanent magnet synchronous machine (IPMSM) model and a state of the art second order sliding mode control (SMC) with four quadrant capability.

Original language	English
Title of host publication	2021 IEEE Vehicle Power and Propulsion Conference, VPPC 2021 - ProceedingS
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781665405287
DOIs	https://doi.org/10.1109/VPPC53923.2021.9699360
Publication status	Published - 2021
Externally published	Yes
Event	18th IEEE Vehicle Power and Propulsion Conference, VPPC 2021 - Virtual, Gijon, Spain Duration: 25 Oct 2021 → 28 Oct 2021

Publication series

Name	2021 IEEE Vehicle Power and Propulsion Conference, VPPC 2021 - ProceedingS

Conference

Conference	18th IEEE Vehicle Power and Propulsion Conference, VPPC 2021
Country/Territory	Spain
City	Virtual, Gijon
Period	25/10/21 → 28/10/21

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

Electric vehicle
Fault detection
Fault diagnosis
Inverter
Permanent magnet synchronous machine
Sliding mode control

Access to Document

10.1109/VPPC53923.2021.9699360

Cite this

Alvarez-Gonzalez, F., Sierra-Gonzalez, A., Trancho, E., & Marcos, M. A. (2021). Online Signal-Based Fault Detection and Diagnosis of EV Inverter during WLTP Driving Cycle. In 2021 IEEE Vehicle Power and Propulsion Conference, VPPC 2021 - ProceedingS (2021 IEEE Vehicle Power and Propulsion Conference, VPPC 2021 - ProceedingS). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/VPPC53923.2021.9699360

Alvarez-Gonzalez, Fernando ; Sierra-Gonzalez, Andres ; Trancho, Elena et al. / Online Signal-Based Fault Detection and Diagnosis of EV Inverter during WLTP Driving Cycle. 2021 IEEE Vehicle Power and Propulsion Conference, VPPC 2021 - ProceedingS. Institute of Electrical and Electronics Engineers Inc., 2021. (2021 IEEE Vehicle Power and Propulsion Conference, VPPC 2021 - ProceedingS).

@inproceedings{ab702fce02ab40219c4bcf6f9953aa94,

title = "Online Signal-Based Fault Detection and Diagnosis of EV Inverter during WLTP Driving Cycle",

abstract = "Recently, transport electrification has undergone a dramatic expansion. This is generating an increasing demand for powertrain reliability. Furthermore, the recent adoption of wide bandgap (WBG) devices, pushes this need even more, particularly for power electronics. This manuscript addresses this need by combining simple and computationally light signal-based fault detection and diagnosis (FDD) methods. These are tested online by simulating electric vehicle (EV) three-phase inverter faults during standardized driving cycles. Simulations are carried out including a three-phase interior permanent magnet synchronous machine (IPMSM) model and a state of the art second order sliding mode control (SMC) with four quadrant capability.",

keywords = "Electric vehicle, Fault detection, Fault diagnosis, Inverter, Permanent magnet synchronous machine, Sliding mode control",

author = "Fernando Alvarez-Gonzalez and Andres Sierra-Gonzalez and Elena Trancho and Marcos, \{Miguel Allende\}",

note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 18th IEEE Vehicle Power and Propulsion Conference, VPPC 2021 ; Conference date: 25-10-2021 Through 28-10-2021",

year = "2021",

doi = "10.1109/VPPC53923.2021.9699360",

language = "English",

series = "2021 IEEE Vehicle Power and Propulsion Conference, VPPC 2021 - ProceedingS",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

booktitle = "2021 IEEE Vehicle Power and Propulsion Conference, VPPC 2021 - ProceedingS",

address = "United States",

}

Alvarez-Gonzalez, F, Sierra-Gonzalez, A , Trancho, E & Marcos, MA 2021, Online Signal-Based Fault Detection and Diagnosis of EV Inverter during WLTP Driving Cycle. in 2021 IEEE Vehicle Power and Propulsion Conference, VPPC 2021 - ProceedingS. 2021 IEEE Vehicle Power and Propulsion Conference, VPPC 2021 - ProceedingS, Institute of Electrical and Electronics Engineers Inc., 18th IEEE Vehicle Power and Propulsion Conference, VPPC 2021, Virtual, Gijon, Spain, 25/10/21. https://doi.org/10.1109/VPPC53923.2021.9699360

Online Signal-Based Fault Detection and Diagnosis of EV Inverter during WLTP Driving Cycle. / Alvarez-Gonzalez, Fernando; Sierra-Gonzalez, Andres ; Trancho, Elena et al.
2021 IEEE Vehicle Power and Propulsion Conference, VPPC 2021 - ProceedingS. Institute of Electrical and Electronics Engineers Inc., 2021. (2021 IEEE Vehicle Power and Propulsion Conference, VPPC 2021 - ProceedingS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Online Signal-Based Fault Detection and Diagnosis of EV Inverter during WLTP Driving Cycle

AU - Alvarez-Gonzalez, Fernando

AU - Sierra-Gonzalez, Andres

AU - Trancho, Elena

AU - Marcos, Miguel Allende

PY - 2021

Y1 - 2021

N2 - Recently, transport electrification has undergone a dramatic expansion. This is generating an increasing demand for powertrain reliability. Furthermore, the recent adoption of wide bandgap (WBG) devices, pushes this need even more, particularly for power electronics. This manuscript addresses this need by combining simple and computationally light signal-based fault detection and diagnosis (FDD) methods. These are tested online by simulating electric vehicle (EV) three-phase inverter faults during standardized driving cycles. Simulations are carried out including a three-phase interior permanent magnet synchronous machine (IPMSM) model and a state of the art second order sliding mode control (SMC) with four quadrant capability.

AB - Recently, transport electrification has undergone a dramatic expansion. This is generating an increasing demand for powertrain reliability. Furthermore, the recent adoption of wide bandgap (WBG) devices, pushes this need even more, particularly for power electronics. This manuscript addresses this need by combining simple and computationally light signal-based fault detection and diagnosis (FDD) methods. These are tested online by simulating electric vehicle (EV) three-phase inverter faults during standardized driving cycles. Simulations are carried out including a three-phase interior permanent magnet synchronous machine (IPMSM) model and a state of the art second order sliding mode control (SMC) with four quadrant capability.

KW - Electric vehicle

KW - Fault detection

KW - Fault diagnosis

KW - Inverter

KW - Permanent magnet synchronous machine

KW - Sliding mode control

UR - https://www.scopus.com/pages/publications/85126216431

U2 - 10.1109/VPPC53923.2021.9699360

DO - 10.1109/VPPC53923.2021.9699360

M3 - Conference contribution

AN - SCOPUS:85126216431

T3 - 2021 IEEE Vehicle Power and Propulsion Conference, VPPC 2021 - ProceedingS

BT - 2021 IEEE Vehicle Power and Propulsion Conference, VPPC 2021 - ProceedingS

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 18th IEEE Vehicle Power and Propulsion Conference, VPPC 2021

Y2 - 25 October 2021 through 28 October 2021

ER -

Alvarez-Gonzalez F, Sierra-Gonzalez A , Trancho E, Marcos MA. Online Signal-Based Fault Detection and Diagnosis of EV Inverter during WLTP Driving Cycle. In 2021 IEEE Vehicle Power and Propulsion Conference, VPPC 2021 - ProceedingS. Institute of Electrical and Electronics Engineers Inc. 2021. (2021 IEEE Vehicle Power and Propulsion Conference, VPPC 2021 - ProceedingS). doi: 10.1109/VPPC53923.2021.9699360

Online Signal-Based Fault Detection and Diagnosis of EV Inverter during WLTP Driving Cycle

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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Cite this