Article
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Preserved in Portico This version is not peer-reviewed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.
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.
Keywords
thermal runaway; big-data platform; battery systems; electric vehicles; National Service and Management Center for Electric Vehicles
Subject
Engineering, Mechanical Engineering
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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