Preprint Article Version 1 This version not peer reviewed

Big-Data-Based Thermal Runaway Prognosis of Battery Systems for Electric Vehicles

Version 1 : Received: 15 May 2017 / Approved: 16 May 2017 / Online: 16 May 2017 (03:18:57 CEST)

A peer-reviewed article of this Preprint also exists.

Hong, J.; Wang, Z.; Liu, P. Big-Data-Based Thermal Runaway Prognosis of Battery Systems for Electric Vehicles. Energies 2017, 10, 919. Hong, J.; Wang, Z.; Liu, P. Big-Data-Based Thermal Runaway Prognosis of Battery Systems for Electric Vehicles. Energies 2017, 10, 919.

Journal reference: Energies 2017, 10, 919
DOI: 10.3390/en10070919

Abstract

This paper presents a thermal runaway prognosis scheme based on the big-data platform and entropy method for battery systems in electric vehicles. It can simultaneously realize the diagnosis and prognosis of thermal runaway caused by the temperature fault through monitoring battery temperature during vehicular operations. A vast quantity of real-time voltage monitoring data was collected in the National Service and Management Center for Electric Vehicles (NSMC-EV) in Beijing to verify the effectiveness of the presented method. The results show that the proposed method can accurately forecast both the time and location of the temperature fault within battery packs. Furthermore, a temperature security management strategy for thermal runaway is proposed on the basis of the Z-score approach and the abnormity coefficient is set to make real-time precaution of temperature abnormity.

Subject Areas

thermal runaway; big-data platform; battery systems; electric vehicles; National Service and Management Center for Electric Vehicles

Readers' Comments and Ratings (0)

Leave a public comment
Send a private comment to the author(s)
Rate this article
Views 0
Downloads 0
Comments 0
Metrics 0
Leave a public comment

×
Alerts
Notify me about updates to this article or when a peer-reviewed version is published.